Agent
Agent Specifications
| Specification | Description |
|---|---|
| Belief System Specification | Defines the internal representation of truth or perceived reality for the agent. This includes what it considers known, assumed, or uncertain, and guides reasoning, learning, and decision-making. |
| Goal System Specification | Outlines the desired outcomes or target states the agent seeks to achieve. Includes goal prioritization, conflict resolution, and reward modeling. |
| Planning Specifications | Specifies how the agent formulates, selects, and executes sequences of actions to achieve goals. Covers action space, temporal dependencies, and optimization strategies. |
| Reasoning Specification | Defines the logic, inference methods, and knowledge structures the agent uses to derive conclusions or make decisions based on beliefs and observations. |
| Exploration Specification | Describes how the agent seeks new information or behaviors, including curiosity, uncertainty-driven exploration, and environmental probing strategies. |
| Adaptiveness Specification | Covers the agent’s ability to adjust its behavior or internal models in response to changing goals, contexts, or environments. This is key to resilience and learning. |
| Intent Specifications | Outlines how the agent expresses or selects intentions based on goals, beliefs, and priorities. Also includes intent resolution and communication to other agents or systems. |
| Infrastructure Specifications | Details the underlying architecture or technical scaffolding that supports agent execution. This includes compute, communication protocols, and resource allocation. |
| Semantics Specifications | Specifies the meaning-making frameworks the agent uses to interpret symbols, concepts, and contexts. This is essential for alignment, language understanding, and ontological interoperability. |
| Trust System Specifications | Defines mechanisms for assessing reliability, safety, and alignment. This applies to both internal (self-trust) and external (trust in other agents, humans, or systems) assessments. |
| Social Specifications | Outlines rules for social interaction, norms, collaboration, and negotiation. Enables collective behavior, multi-agent coordination, and ethical alignment in shared environments. |
| Environment Specifications | Describes the external operating context for the agent, including assumptions about sensors, actions, boundaries, affordances, and environment dynamics. |
Agentic network Modes
| Mode | Description |
|---|---|
| Individual | Agents operate autonomously with no explicit interaction or awareness of others. Each agent pursues its own goals based on its internal specifications, making decisions in isolation. |
| Coordinated | Agents collaborate or communicate with one another to align on shared goals, distribute tasks, or manage interdependencies. Involves collectively problem solving via coordinated planning, reasoning, intent signaling, and role negotiation. Coordination can be centralized or decentralized. |
| Modeling | Agents form internal models of other agents, environments, or the overall system to improve prediction, adaptation, or strategic planning. This allows agents to simulate possible outcomes, anticipate others’ actions, or infer hidden dynamics. |
| Simulation | Multiple agents interact within a shared environment to test hypotheses, explore behaviors, strategize or learn under controlled conditions. This mode is often used for scenario analysis, multi-agent experimentation, or large-scale environment probing. |
Agent Core Systems
Belief System
| Component | Description |
|---|---|
| Belief Base | Stores all known and inferred beliefs an agent holds about itself, the world, and others. |
| Belief Schema | Defines the structure and type system used to organize and interpret beliefs. |
| Belief Specification | Outlines formal representations, formats, and logical models that qualify as valid beliefs. |
| Belief Acquisition | Mechanisms through which beliefs are gathered, including sensors, external data, or other agents. |
| Belief Update | Processes that revise beliefs based on new evidence or changes in context. |
| Belief Confidence Estimator | Assesses the reliability or certainty of each belief, factoring in data quality and source credibility. |
| Source Attribution Module | Tracks the origin of each belief to support transparency, traceability, and trust. |
| Temporal Belief Tracker | Maintains a history of belief changes and time-stamped updates to handle evolving information. |
| Consistency Checker | Ensures logical consistency across the belief base to avoid contradiction or invalid inference. |
| Belief Access Interface | Provides a standardized way for internal modules or external systems to query or access beliefs. |
| Belief Sharing Protocol | Handles how beliefs are communicated, exchanged, or synchronized across agents or systems. |
Goal System
| Component | Description |
|---|---|
| Goal Repository | Stores active, pending, or archived goals across different time horizons and priorities. |
| Goal Activator | Determines when a dormant or latent goal should be activated based on context or triggers. |
| Goal Generator | Synthesizes new goals from internal states, reasoning processes, or external signals. |
| Goal Decomposer | Breaks down complex goals into smaller, more manageable sub-goals or tasks. |
| Goal Controller | Manages execution and progress tracking of currently active goals. |
| Goal Prioritization | Ranks and selects goals based on urgency, value, feasibility, or agent policy. |
| Goal Conflict Resolver | Identifies and resolves conflicts between competing or contradictory goals. |
| Goal Monitoring | Continuously tracks goal progress, success criteria, and environmental alignment. |
| Goal Evaluation | Assesses the outcome of completed goals for learning, feedback, or future planning. |
| Goal Adaptation | Modifies goals mid-execution in response to dynamic changes or partial failures. |
| Goal Communication Interface | Enables goals to be shared, delegated, or negotiated between agents or systems. |
| Goal Coordination | Supports synchronization and collaboration across agents with interdependent goals. |
Planning System
| Component | Description |
|---|---|
| Plan Generator | Creates one or more potential plans to achieve a given goal. |
| Plan Sourcing | Retrieves reusable or external plans from repositories or shared libraries. |
| Plan Registry | Stores created and approved plans for tracking, reuse, and analysis. |
| Plan Evaluator | Assesses each plan's feasibility, efficiency, and alignment with constraints. |
| Plan Selector | Chooses the best-fit plan from evaluated options based on defined criteria. |
| Approval / Consensus | Handles plan acceptance through internal checks or multi-agent agreement mechanisms. |
| Plan Monitor | Tracks the execution of plans in real time, including progress, interruptions, and deviations. |
| Contingency Manager | Handles fallback procedures or safety mechanisms if the current plan fails. |
| Replanner | Dynamically revises or regenerates plans when unexpected changes occur. |
| Plan Controller | Orchestrates the implementation and execution flow of the selected plan. |
Reasoning System
| Component | Description |
|---|---|
| Knowledge Base Interface | Connects reasoning mechanisms to stored knowledge structures, enabling logical access to facts, rules, and learned representations. |
| Rule Base / Logic Model | Houses the formal logic or rule sets used to drive deterministic or structured reasoning processes. |
| Inference Engine | Executes logical deductions or inferences based on available knowledge and reasoning strategies. |
| Heuristic Engine | Applies heuristic methods for faster or approximate reasoning, useful in resource-constrained or complex scenarios. |
| Context Manager | Maintains and updates situational context relevant to reasoning, including temporal, spatial, or task-specific frames. |
| Consistency Manager | Ensures internal coherence across reasoning outputs by validating against known facts and logic constraints. |
| Reasoning Strategy Registry | Stores various reasoning modes (e.g., deductive, abductive) available to the agent for selection or switching. |
| Reasoning Strategy Evaluator | Assesses the performance or fit of different reasoning strategies based on accuracy, efficiency, or contextual relevance. |
| Reasoning Strategy Selector | Chooses the most appropriate reasoning approach dynamically, based on agent state, task, or environment. |
| Counterfactual Simulator | Allows the agent to simulate alternate outcomes by changing assumptions, aiding in causal reasoning and planning. |
| Backtracking | Supports reversible reasoning paths by undoing inference steps when contradictions or dead ends are detected. |
| Uncertainty Manager | Quantifies and manages uncertainty in reasoning outputs, enabling probabilistic or fuzzy inference mechanisms. |
Exploration System
| Component | Description |
|---|---|
| Exploration Policy Registry | Stores a library of strategies for exploring unknowns, such as curiosity-driven, uncertainty-based, or goal-guided approaches. |
| Exploration Policy Selector | Selects the most suitable exploration policy in response to task needs, novelty signals, or environment cues. |
| Exploration Policy Manager | Oversees execution, switching, and evaluation of exploration policies throughout an agent’s operation. |
| Novelty Detector | Identifies unfamiliar states, inputs, or patterns that may warrant attention or learning updates. |
| Budget Controller | Manages exploration cost in terms of time, compute, or risk, balancing it with overall resource constraints. |
| Exploration vs. Exploitation Balancer | Modulates when to pursue new knowledge versus leveraging known strategies for performance optimization. |
| Exploration Logger | Tracks exploration events, outcomes, and coverage to support auditability and future planning. |
| Risk Manager / Safety Filter | Filters out unsafe exploratory actions and applies constraints to minimize harm during novelty-seeking behaviors. |
| Social Exploration | Coordinates exploration with or through other agents, leveraging shared knowledge or observations to expand discovery. |
Adaptiveness System
| Component | Description |
|---|---|
| Change Detection | Monitors the environment or internal agent state for shifts that require behavioral or structural adaptation. |
| Feedback Integrator | Consolidates external feedback and internal signals to inform adjustment processes. |
| Adaptation Control Logic | Governs the process of deciding whether, when, and how to apply adaptation procedures. |
| Plasticity Manager | Manages the agent’s structural flexibility, allowing reconfiguration of capabilities or decision pathways. |
| Adaptive Planning Integrator | Aligns adaptation processes with ongoing planning activities, ensuring continuity and goal coherence. |
| Resilience Evaluator | Measures the agent’s robustness under stress or failure conditions and suggests mitigations. |
| Behavior Modifier | Dynamically alters behavioral patterns based on recent outcomes or evolving goals. |
| Self-Tuning Engine | Continuously adjusts parameters or internal models to improve efficiency, alignment, or stability. |
| Adaptation Memory | Stores prior adaptation cases and results to support meta-learning and reapplication. |
| Adaptation Selection | Chooses which adaptation strategy or method to apply given current constraints and opportunities. |
| Adaptations Registry | Maintains a catalog of all possible or historically used adaptation mechanisms. |
| Adaptation Constraints Module | Defines boundaries and safety limits for acceptable adaptation actions. |
| Look Ahead System | Projects the outcomes of different adaptation paths before commitment, aiding foresight and risk assessment. |
Knowledge System
| Component | Description |
|---|---|
| Knowledge Bases | Repositories where structured and unstructured knowledge, reflecting its role, beliefs, goals, and environment is stored for access and reasoning by the agent. |
| Ontology Manager | Maintains the formal structure and relationships between concepts, ensuring semantic consistency across the agent's knowledge. |
| Knowledge Acquisition Engine | Enables the agent to actively gather new knowledge from data, interaction, or observation, enriching its internal models. |
| Knowledge Representation Engine | Translates raw data or structured inputs into formal representations suitable for reasoning and storage. |
| Knowledge Retrieval Engine | Fetches relevant knowledge elements on demand to support decision-making, planning, or interpretation tasks. |
| Knowledge Revision / Removal | Handles the correction, pruning, or deletion of outdated or invalid knowledge entries to maintain relevance. |
| Contextual Knowledge Provider | Supplies task- or situation-specific knowledge in real time to adapt behavior based on the surrounding context. |
| Knowledge Sharing Interface | Facilitates interoperability and exchange of knowledge between agents or systems using standardized protocols. |
| Episodic Memory Manager | Stores and manages time-bound experiences or events for retrospective analysis and learning. |
| Meta-Knowledge | Maintains knowledge about knowledge itself, understanding about how knowledge is structured, used, updated, or shared. |
Curriculum System
| Component | Description |
|---|---|
| Static Curriculum | A predefined sequence of tasks or learning modules used to train or guide agent development in fixed contexts. |
| Dynamic Curriculum | Adapts the sequence or difficulty of tasks in real time based on agent performance, environment, or goals. |
| Emergent Curriculum | An evolving structure of tasks, behaviors, and opportunities that emerges from the agent’s interactions with its environment, other agents, and internal feedback. |
| Self Curriculum | A dynamic, self-evolving framework that guides how the agent selects, sequences, and adapts internal processes such as learning, behavior, resource use, or replication based on context, goals, and feedback. |
| Planning Curriculum | Focuses on progressively enabling the agent how to construct, evaluate, and refine plans. |
| Reasoning Curriculum | Builds the agent’s ability to apply logical, heuristic, or analogical reasoning across increasingly complex scenarios. |
| Belief Curriculum | Guides the agent on how to form, evaluate, and update beliefs in dynamic or uncertain environments. |
| Exploration Curriculum | Guides the agent in developing effective exploration strategies and understanding exploration vs. exploitation tradeoffs. |
| Exploitation Curriculum | Emphasizes leveraging learned strategies and optimizing behaviors based on stable or known conditions. |
| Adaptiveness Curriculum | Agent’s abilities to adjust its policies, strategies, and beliefs in response to change or disruption. |
| Social Curriculum | Equips on norms, conventions, and strategies for engaging with other agents or humans in shared environments. |
| Decision Curriculum | Builds the agent's capability to evaluate options, manage uncertainty, and make rational decisions under constraints. |
| Action Curriculum | Defines the evolving sequence through which the agent selects, assembles, activates, and refines goal-directed or reactive actions |
| Behaviour Curriculum | Outlines the progression through which the agent stabilizes and modulates behavioral skills to align with roles, social, system & environment contexts |
| Coalition Curriculum | Prepares the agent to collaborate, align, and form cooperative structures with other agents. |
| Negotiation Curriculum | Builds competence in multi-agent negotiation, including offers, counteroffers, and agreement resolution. |
Trust System
| Component | Description |
|---|---|
| Trust Modeling Engine | Constructs formal models of trust relationships based on historical interactions, performance, and alignment. |
| Reputation Manager | Tracks agent reputation over time, aggregating public or peer feedback to inform trust evaluations. |
| Feedback Provider | Supplies structured or unstructured feedback signals that inform behavior adjustments and trust updates. |
| Trust Policy Engine | Encodes the policies and criteria used by the agent to assess and act upon trust-related decisions. |
| Behavior Monitor | Observes and records agent behavior to evaluate consistency with expectations and norms. |
| Risk Assessment Module | Analyzes potential risks in agent interactions, decisions, or environments that affect trustworthiness. |
| Evidence Collector | Gathers supporting data or justification to validate claims, actions, or system reliability. |
| Alignment Verifier | Checks that the agent’s actions and objectives remain consistent with external values, ethics, or contracts. |
| Trust Propagation | Mechanisms to share or extend trust assessments across networks or hierarchies of agents. |
| Transparency Estimator | Evaluates how interpretable or explainable the agent’s internal processes are to observers or collaborators. |
Social System
| Component | Description |
|---|---|
| Agents Awareness Engine | Maintains awareness of other agents in the environment, including identities, states, and proximity, to enable social reactivity. |
| Social Graph Manager | Manages dynamic relationships between agents, encoding trust, communication, roles, and shared histories as graph structures. |
| Role Manager | Assigns, negotiates, and updates agent roles within groups or social contexts based on task needs and agent attributes. |
| Norms & Protocol Compliance | Ensures that the agent adheres to predefined behavioral norms, ethical rules, and multi-agent interaction protocols. |
| Social Goal Manager | Handles goals that require or benefit from social interaction, such as cooperation, persuasion, or influence. |
| Social Inference | Interprets the intentions, goals, or emotional states of others through observation or communication signals. |
| Coordination Engine | Synchronizes actions and decisions across agents to ensure coherent group behavior and minimize conflict. |
| Communication Interface | Facilitates structured message exchange with other agents or humans using shared vocabularies or protocols. |
| Group Formation | Manages dynamic creation, joining, or restructuring of groups based on shared objectives or compatibility. |
| Social Culture Engine | Models and applies culturally-specific behaviors, customs, or adaptations in multi-agent or human-agent environments. |
Drive System
| Component | Description |
|---|---|
| Objectives | Represents high-level goals or directional preferences that shape agent motivation and long-term behavior. |
| Drive State | A dynamic representation of internal needs such as Curiosity, Competence, Safety, Social, Resource scarcity |
| Homeostasis Controller | Ensures balance and regulation across drivers in response to stress, overload, or instability. |
| Drive-to-Goal Translator | Converts raw drive signals into actionable, goal-oriented actions the agent can pursue. |
| Drive Selector | For a given context scenario, chooses among internal drives or ranks competing drives based on priority. |
| Intrinsic Drive Engine | Generates goals or actions based on internal rewards, curiosity, novelty, or autonomy-related triggers, not external rewards |
| Extrinsic Drive Engine | Responds to external stimuli such as rewards, punishments, or social reinforcement mechanisms. |
| Drive Adaptation | Adjusts the intensity, threshold, or prioritization of drives over time based on outcomes or changing conditions. |
| Objective Optimizer | Continuously refines how objectives are represented and pursued to improve performance and alignment. |
Learning System
| Component | Description |
|---|---|
| Reflections & Feedback | Performs post-task analysis and external feedback to refine agent strategies, beliefs, or behaviors. |
| Experience Memory | Stores experiential data from past interactions, enabling reuse and learning from real-world events. |
| Curriculum Manager | Orchestrates the learning sequence and progression based on current capabilities, tasks, and goals. |
| Learning Policy Selector | Dynamically selects among available learning strategies depending on task type, agent state, or context. |
| Model Trainer / Updater | Trains or fine-tunes the internal models used for prediction, planning, or decision-making. |
| Performance Evaluator | Monitors learning outcomes, measuring effectiveness, generalization, and improvement over time. |
| Meta-Learning System | Enables the agent to learn how to learn by analyzing learning patterns, strategy effectiveness, and knowledge gaps. |
| Self Assessment Engine | Allows the agent to internally evaluate its knowledge, performance, or preparedness without external input. |
| Lifelong Learning Manager | Ensures continuity and accumulation of learning throughout the agent's operational lifespan. |
| Social Learning Interface | Supports acquiring knowledge or behaviors from observing or interacting with other agents. |
Action System
| Component | Description |
|---|---|
| Actions Registry | Stores a library of known, valid, and executable actions the agent can choose from during runtime. |
| Action Evaluator | Assesses potential actions based on effectiveness, cost, safety, and alignment with current goals. |
| Action Selector | Chooses the most appropriate action from available options, considering policy, utility, and situational constraints. |
| Action Parameterizer | Instruments the actions or Adjusts action parameters such as intensity, duration, or scope to suit the current task or environment. |
| Action Execution | Responsible for carrying out the selected action through interfacing with systems, or APIs. |
| Action Monitor | Tracks execution status and performance, detecting delays, deviations, or anomalies during action implementation. |
| Failure Handler | Responds to failed or interrupted actions by triggering recovery mechanisms or fallback strategies. |
| Action Constraints & Safety | Enforces physical, logical, or ethical constraints to ensure that actions are within safe operating bounds. |
| Action Outcome Logger | Records execution results and contextual metadata for traceability, learning, and future evaluation. |
| Backtracking | Reverses or rolls back actions when undesirable outcomes occur or when reevaluation is needed. |
| Action Feedback | Captures feedback from action outcomes to inform learning, policy updates, or adaptive planning. |
Decision System
| Component | Description |
|---|---|
| Input Aggregation | Combines information from diverse sources to form a comprehensive input set for decision-making. |
| Context Modeling | Builds a contextual frame that informs and constrains decisions based on environmental, temporal, or social data. |
| Reasoning Engine | Applies logical or heuristic processes to derive implications and guide the decision path. |
| Decision Logic Engine | Encodes the decision-making policies, rules, or utility functions used to arrive at final choices. |
| Social Choice Engine | Implements voting, ranking, or consensus mechanisms for decisions involving multiple agents or stakeholders. |
| Multi-Agent Consensus | Enables collective agreement formation among agents, especially in decentralized or distributed settings. |
| Dictatorial Decision | Executes decisions unilaterally, useful in critical or time-sensitive scenarios where consensus is impractical. |
| Collective Decision | Derives decisions from shared input and agreement among participating agents or subsystems. |
| Decision Memory & Feedback | Maintains a historical record of past decisions, contexts, and outcomes to support reflective improvement. |
| Decisions Selector | Picks from multiple candidate decisions based on priority, outcome probabilities, or external input. |
| Decisions Registry | Stores all finalized decisions for future retrieval, explanation, or auditing. |
Human-in-the-Loop (HIL) System
| Component | Description |
|---|---|
| Human Interaction Interface | Enables structured communication and collaboration between the agent and human users. |
| Human Task Assignment | Allocates tasks to humans based on expertise, load balancing, or supervisory protocols. |
| Escalation Engine | Triggers human intervention when the agent encounters uncertainty, conflict, or failure conditions. |
| Override by Human | Provides humans the ability to intervene, modify, or cancel agent actions or decisions in real time. |
| Autonomous Level Config. | Allows tuning of autonomy levels, ranging from fully autonomous to tightly supervised modes. |
| Role-Based Routing System | Routes decision points or information to specific human roles based on responsibility or domain expertise. |
| Human as Decision Support | Uses human input to supplement or validate the agent’s decision process, particularly in edge cases. |
| Human Feedback Integration | Incorporates explicit or implicit human feedback into belief, behavior, or policy updates. |
| Human Annotation Integration | Allows humans to tag, annotate, or label data for improving agent's performance and grounding. |
| Action Approval | Requires explicit human sign-off before executing sensitive or high-stakes actions. |
| Dual Control / Co Decision | Combines human and agent input in a shared decision-making model to ensure accountability. |
| Kill-Switch | Provides a hard-stop mechanism for humans to immediately halt all agent operations. |
| Watch Dog | Continuously monitors agent behavior and flags anomalies or violations for human review or intervention. |
Behavior
Operational Behaviors
| Behavior | Description |
|---|---|
| Self Replication | Enables the agent to spawn clones or instances of itself to scale operations or parallelize tasks. |
| Human in Loop | Integrates human oversight or intervention into operational processes for supervision or decision overrides. |
| Retirement / Terminate | Shuts down or decommissions the agent when no longer needed, preserving resources or avoiding risk. |
| Onboarding | Initializes an agent into a network or task environment, including configuration and identity setup. |
| Distribution | Allocates tasks, data, or responsibilities across nodes or agents in a system. |
| Delegation | Assigns tasks or responsibilities to another agent or subsystem to offload work. |
| Escalation | Transfers control or raises issues to a higher-level authority or supervisory process. |
| Memberships | Manages participation in groups, organizations, or roles that define collaboration rights. |
| Join | Allows an agent to enter a new network, environment, or multi-agent system. |
| Migration | Moves the agent or its processes between locations, platforms, or organizational contexts. |
| Self-Diagnostics | Monitors internal systems for faults or suboptimal performance. |
| Self-Healing | Triggers automatic recovery or repair mechanisms when errors or degradation are detected. |
| Action Execution | Carries out chosen operations or interactions as part of active behavior. |
| Role Switching | Dynamically changes the agent’s function or identity within a social or task context. |
| Suspend / Sleep | Temporarily pauses activity to conserve energy, resources, or wait for external triggers. |
| Resume / Wake | Reactivates the agent from a dormant state when needed. |
| Spawn | Initiates a new agent instance or subprocess to increase capacity or distribute effort. |
| Reconfigure | Alters the internal structure or external connections of the agent to fit changing needs. |
| Sandbox | Isolates execution for safety, testing, or containment of high-risk actions. |
| Authorization / Authentication | Validates identity and access rights before critical operations are executed. |
Social Behaviors
| Behavior | Description |
|---|---|
| Hiring / Scouting | Searches for agents or resources to fulfill specific roles or tasks or augment capabilities. |
| Contracting | Establishes formal agreements between agents or agencies regarding task execution or resource sharing. |
| Approvals | Seeks and processes validation from other agents or humans before proceeding. |
| Exploration | Initiates curiosity-driven or directed discovery activities, often with social input. |
| Outsourcing | Assigns tasks to external agents or systems to offload load or access expertise. |
| Application | Submits offers or expresses interest in participating in tasks, coalitions, or groups. |
| Accepting | Acknowledges and commits to tasks, roles, or relationships proposed by others. |
| Rejecting | Declines offers, requests, or social bindings based on policy or strategic considerations. |
| Negotiation | Engages in back-and-forth exchanges to reach mutually acceptable agreements. |
| Feedback | Provides structured responses or evaluations to support learning or refinement. |
| Supervising | Oversees the behavior or performance of other agents, providing guidance or correction. |
| Reputation / Trust | Engages in behaviors that manage, assess, or leverage social credibility or reliability. |
| Sourcing | Locates and evaluates available agents, resources, or services. |
| Agency Association | Aligns with particular agent networks or collectives to access shared capabilities or collaboratively solve tasks. |
| Coalition | Form temporary or long term alliances to pursue shared goals, pooling resources and strengths while maintaining individual autonomy. |
| Coordination | Agents align timing, actions, and plans to ensure smooth execution without conflict or redundancy across tasks or roles. |
| Cooperation | Agents actively work together, sharing information and tasks to achieve a common, mutually beneficial goal that they cannot attain individually. |
| Compete | Agents pursue overlapping or conflicting goals, often optimizing for individual advantage in shared environments. |
| Discussion | Agents exchange information, perspectives, and arguments to understand problems, negotiate options, or reach consensus. |
| Orchestrate | Directs the behavior of multiple agents toward a common performance or workflow. |
| Signal | Sends explicit or implicit messages that influence others' behavior or perceptions. |
| Communicate | Exchanges information, intentions, or states using formal or informal protocols. |
| Align | Adjusts behavior or goals to match those of a group, leader, or policy. |
| Deliberate | Engages in careful reasoning or consultation before making social or task decisions. |
Cognitive Behaviors
| Behavior | Description |
|---|---|
| Decision Making | Selects among available options using internal logic, utility functions, or probabilistic models. |
| Adapting | Modifies beliefs, strategies, or behaviors in response to environmental or internal changes. |
| Planing | Constructs structured sequences of actions to achieve a desired goal or state. |
| Mind Selection | Chooses among available AI models or cognitive architectures as agents brain based on task needs. |
| Belief Update | Modifies or refines beliefs in response to new evidence or reasoning outcomes. |
| Memory Update | Adds, removes, or modifies stored knowledge to reflect new experiences or revisions. |
| Goal Selection | Identifies which among many possible goals should be pursued next. |
| Intent Recognition | Detects or infers the likely goals or motives of other agents or humans. |
| Self Monitoring | Continuously evaluates internal performance, resource use, and behavior quality. |
| Memory Management | Organizes how information is stored, retrieved, and discarded over time. |
| Identity Awareness | Maintains understanding of the agent's own identity, role, and boundaries across different contexts. |
| Exploration | Initiates curiosity-driven behavior to acquire new knowledge or expand boundaries. |
| Perception | Processes sensory input to form internal representations of the environment. |
| Reflection / Critic | Examines past decisions or performances to extract learning or identify errors. |
| Reasoning | Applies logical, analogical, or probabilistic inference to generate conclusions. |
| Revision | Revises knowledge structures, models, or policies in light of error or updated information. |
| Action Selection | Chooses the next action from a set of options based on reasoning and current context. |
| Personality | Expresses consistent patterns of cognitive-emotional traits influencing behavior style. |
| Belief Formation | Creates new beliefs from observations, reasoning, or interaction with others. |
| Problem Solving | Applies structured or creative strategies to resolve obstacles or achieve goals. |
| Learning | Acquires new knowledge, behaviors, or skills through experience, instruction, or reflection. |
| Prioritize | Orders tasks, goals, or decisions based on value, urgency, or importance. |
| Skill Acquisition | Gains new capabilities through mindselection, training, experience, or imitation. |
| Self Evolution | Advances its own design, goals, or capabilities through introspective and meta-level change. |
| Self Improvement | Incrementally enhances its own performance, adaptability, or understanding over time. |
| Strategy | Develops high-level plans or meta-policies for long-term goal pursuit and resilience. |
Memory Behaviors
| Behavior | Description |
|---|---|
| Encode | Converts raw inputs into structured memory formats that preserve meaning, relationships, and context for future use. |
| Index | Assigns identifiers or metadata or lookup keys to memory entries to enable efficient search, filtering, and contextual retrieval. |
| Update | Revises existing memory entries with fresher data or corrected interpretations to maintain alignment with current knowledge. |
| Annotate | Adds semantic labels, notes, or tags to memories to enrich interpretation and enable cross-context referencing. |
| Share | Enables memory segments to be transmitted or exposed to other agents or systems to support collaboration or alignment. |
| Search | Performs queries across memory to locate specific information or patterns. |
| Recall / Retrieve | Fetches previously stored information into working memory for active reasoning, action, or learning. |
| Match | Compares new inputs to stored patterns or instances to detect similarity or known patterns. |
| Replay | Reconstructs past sequences of events or decisions for analysis or reflection. |
| Consolidate | Merges short-term or fragmented memories into structured, stable, long-term representations for reliability. |
| Organize | Arranges memory entries by time, topic, hierarchy, clusters or usage frequency to improve efficiency and access. |
Technical Behaviors
| Behavior | Description |
|---|---|
| Research | Conducts structured investigation using data collection, hypothesis testing, and analysis to generate or refine knowledge. |
| Retrieve | Accesses internal or external sources to obtain specific knowledge, models, or tools required for task execution. |
| Coordination | Aligns the timing, goals, and actions of concurrent processes or agents to ensure task efficiency and conflict avoidance. |
| Clone / Fork | Duplicates agent instances or logic branches to support parallel exploration, redundancy, or architectural experiments. |
| Merge / Fusion | Integrates multiple data, models, or processes into a unified framework that improves consistency or insight. |
| Observe, Trigger, Action | Monitors conditions continuously and activates predefined responses or workflows when triggers are detected. |
| Function Calling | Invokes specific programmatic routines or agent functions using defined interfaces and input-output protocols. |
| Tool Calling | Interfaces with third-party software or utilities to perform specific actions beyond native agent capabilities. |
| Code Execution | Runs internal or user-defined scripts and logic to compute, manipulate data, or generate new behaviors dynamically. |
| Goal Seeking | Actively searches for viable and meaningful goals to pursue based on internal drives, policies, or observations. |
| Goal Abandonment | Discontinues current goal pursuit when it becomes irrelevant, conflicting, or too costly to justify continuation. |
| Collaboration | Works jointly with other agents or systems by aligning tasks, goals, and interfaces for shared objectives. |
| Competition | Engages in adversarial dynamics where resources, status, or outcomes are limited and contested. |
| Social Signaling | Emits observable cues or metadata that inform others of internal states, intentions, or readiness. |
| Norm Following | Adheres to shared social, ethical, or procedural rules that govern acceptable behavior in collective environments. |
| Conflict Resolution | Identifies and resolves disputes, overlaps, or contradictions between tasks, agents, or processes. |
| Fall-back | Switches to secondary plans or safe defaults when primary plans fail or environment conditions change unexpectedly. |
| Goal Alignment | Ensures agent behaviors and choices are consistently directed toward and harmonized with high-priority goals. |
| Observer Mode | Operates passively to collect information and learn from ongoing events without direct intervention or control. |
| Teacher Mode | Engages in structured behavior to guide, instruct, or transfer knowledge to other agents or human users. |
| Repair | Diagnoses and fixes malfunctions in internal modules, logic structures, or external interactions. |
| Information Sharing | Actively disseminates knowledge, experiences, or decisions to improve system-wide performance and awareness. |
| Consensus Seeking | Facilitates collective agreement across agents by aligning perspectives, preferences, or strategies. |
| Priority & Overriding | Adjusts priority levels of competing tasks or interrupts active flows when urgent or critical needs arise. |
Social Choice Behaviors
| Behavior | Description |
|---|---|
| Aggregation | Collects and combines data, opinions, or scores from multiple agents to form a representative group output. |
| Voting | Allows agents or users to rank or select among alternatives through majority, weighted, or consensus-based ballots. |
| Collective | Supports shared decisions derived from distributed agents without centralized control, often through emergence. |
| Fairness & Justice | Applies equity-focused rules to ensure decisions are just, balanced, and inclusive of diverse agent values. |
| Argumentation | Engages in logical dialogue or debate to justify claims, challenge assertions, or persuade other agents. |
| Election | Implements selection processes where candidates or outcomes are chosen through structured voting or nomination. |
| Veto | Enables individuals or minority agents to block proposals that violate thresholds or critical principles. |
| Deliberation | Facilitates extended, rational discussion among agents or humans to weigh trade-offs and refine judgments. |
| Sortition | Randomly selects participants or leaders to ensure diversity, prevent bias, or manage workloads. |
| Constraint Satisfaction | Identifies solutions that satisfy multiple overlapping agent preferences, constraints, or ethical bounds. |
Regulated Behaviors
| Behavior | Description |
|---|---|
| Function Calling | Invokes defined operations or capabilities within or outside the agent system in response to rule-triggered events. |
| Tool Calling | Connects to and utilizes external tools or modules with regulated access and logged interactions for traceability. |
| Interrupts | Halts, suspends, or overrides an agent's execution flow due to regulatory triggers or safety constraints. |
| Actions | Executes operations that comply with policy constraints, runtime conditions, and permission scopes. |
| Events | Responds to internal or external events by initiating approved workflows or state transitions. |
| Communications | Sends and receives messages under governed protocols ensuring policy, logging, and permissions. |
| Decisions | Makes choices within specified policy bounds, sometimes requiring additional approvals or triggers. |
| Cognitive Calls | Invokes higher-order cognitive modules, such as planners or reasoners, under governed permissions. |
| Access | Controls entry to protected resources or spaces based on authentication, delegation, or clearance. |
| Memory | Regulates what gets stored, shared, recalled, or erased in memory based on ethical or security policy. |
| Knowledge | Governs acquisition, use, and sharing of knowledge artifacts based on context-sensitive policy frameworks. |
| Mutation | Permits structural changes to agent logic or behaviors, constrained by version control and rollback protocols. |
| Replication | Enables agent duplication for scaling or redundancy, gated by budget, permissions, and risk parameters. |
| Self Modulation | Adjusts internal regulatory thresholds such as effort, focus, or response rate based on monitored limits. |
| Budgets | Allocates time, resource, or energy budgets for bounded behavior execution under governance limits. |
| Self Regulation | Monitors internal states to stay within ethical or operational boundaries autonomously. |
| System Access | Controls access to system interfaces, resources and system manipulation in shared agent systems. |
| Deviations | Logs or mitigates any actions or paths taken that fall outside allowed behavioral ranges or standards. |
| Delegations | Transfers regulated responsibility to other agents or modules with traceable scopes and revocation control. |
Economic Behaviors
| Behavior | Description |
|---|---|
| Create | Generates novel artifacts, services, or intellectual outputs of economic or collaborative value. |
| Transform | Converts raw data, energy, or inputs into more useful or refined outputs for further use or exchange. |
| Compose/Assemble | Integrates multiple parts, services, or modules into a functioning whole or service offering. |
| Trade | Exchanges resources, assets, or services with other agents using agreed-upon value representations. |
| Bid | Submits competitive offers in auctions or marketplaces to obtain resources, contracts, or attention. |
| Buy | Acquires services, tools, or knowledge from other agents through value-based transactions. |
| Offer | Makes available certain resources or services for others to engage with or acquire. |
| Distribute | Delivers or allocates products, services, or data among agents in accordance with contracts or rules. |
| Syndicate | Pools value, intent, or effort with others to increase collective impact or access shared rewards. |
| Utilize | Applies acquired or shared resources toward a productive or goal-oriented outcome. |
| Contracts | Establishes binding economic agreements with rules for exchange, timelines, failure handling, and rewards. |
Governance Behaviors
| Behavior | Description |
|---|---|
| Propose | Initiates a new rule, structure, or suggestion to be evaluated or voted on by other agents. |
| Vote | Participates in governance decisions using voting rights defined by roles, stakes, or group rules. |
| Register | Officially logs presence, identity, resources, or proposals into shared governance systems. |
| Authenticate | Validates identity, credentials, or authority before allowing access or participation. |
| Enforce | Applies and upholds agreed policies, ensuring consequences for non-compliance are implemented. |
| Compliance | Adheres to rules, policies, or external regulations by adjusting behavior dynamically. |
| Escalate | Raises issues or decisions to higher authority or group levels when local resolution fails. |
| Dispute | Challenges existing rules, actions, or decisions using structured debate or formal processes. |
| Consent / Dissent | Explicitly agrees with or rejects proposals. |
| Verify | Confirms truth, consistency, or authenticity of facts, behaviors, or signatures in governance flow. |
| Evaluate | Assesses performance, outcomes, impact, or fairness of participants or governance policies. |
| Audit | Reviews, traces, and reports on decisions, data, and actions for transparency and accountability. |
Collaboration Behaviors
Consensus-Based
| Behavior | Description |
|---|---|
| Discussing | Exchanges views and data in a structured dialogue to build mutual understanding. |
| Debating | Engages in argumentative exchanges that weigh evidence, values, and outcomes to influence or refine ideas. |
| Negotiation | Navigates conflicts or differences in preferences to find mutually acceptable agreements. |
| Reflecting | Examines prior decisions, actions, or beliefs to draw insights or re-align group perspectives. |
| Voting | Participates in collective decision processes to reflect shared preferences or commitments. |
Collaborative Learning
| Behavior | Description |
|---|---|
| Experience Sharing | Transmits past experiences or case studies to enhance group knowledge and collective intelligence. |
| Teaching / Mentoring | Provides structured instruction or guidance to help others develop competencies or understanding. |
| Discussions | Hosts or joins structured knowledge dialogues for discovery, synthesis, and reflection. |
| Criticism / Feedback | Evaluates peer behaviors or outputs constructively to improve accuracy, style, or direction. |
| Evaluation | Assesses knowledge, performance, or proposals collaboratively to validate or improve them. |
| Instructing | Delivers precise procedural or conceptual guidance to shape peer or system behavior effectively. |
Agent Lifecycle Management
Initialization & Formation
| Component | Description |
|---|---|
| Identity Assignment | Assigns a unique identity to the agent, enabling traceability, authentication, and network wide recognition. |
| Genesis Protocols | Executes the initial setup protocols that define how the agent is born, configured, and bootstrapped into the environment. |
| Initial Resource Allocation | Provides agents with startup resources, such as compute, memory, access keys, or capabilities needed for basic functioning. |
| Foundational Roles | Establishes the agent's primary functions or missions that guide its initial objectives and responsibilities. |
| Contracts / Code Instantiation | Deploys the agent’s smart contracts or runtime logic that binds it to system rules and execution capabilities. |
| Infra. Spawning | Initiates computing substrate or infrastructure for agent's role with required connectivity, interfaces, and dependencies. |
| Agent Registration | Registers the agent with identity, metadata, or policy registries to enable discovery, tracking, and authorization. |
| Log Initiation | Begins logging critical state, behavior, and decisions for traceability, audit, and introspection from first run onward. |
Structural Composition
| Component | Description |
|---|---|
| Role & Capability Definition | Defines what the agent can do and under which roles, enabling alignment with operational or governance expectations. |
| Governance Definition | Specifies how the agent is governed, whether autonomous, participatory, or subject to external rule sets. |
| Sub Agent Topology | Structures internal agent clusters or modules, specifying delegation, sub-routine boundaries, and communication paths. |
| Topology Models | Outlines inter-agent configurations such as mesh, hierarchy, or hub-and-spoke structures to guide interactions. |
| Agent Archetypes | Establishes reusable blueprints or behavioral classes agents can inherit from to reduce duplication and enforce norms. |
Operation & Execution
| Component | Description |
|---|---|
| State Management | Tracks and manages agent status, memory, resource claims, and runtime variables essential to continuity and decision-making. |
| Health Monitoring | Continuously evaluates agent performance, reliability, and anomaly signals to enable self-repair or intervention. |
| Agent Scheduling | Manages agent activation, task execution timing, load balancing, and multi-agent orchestration timelines. |
| Resource Management | Allocates and monitors usage of memory, compute, APIs, or other quotas to ensure sustainable execution. |
| Supervisor / Supervision | Applies oversight systems or supervisory agents that can intervene, redirect, or reset behavior based on goals or policies. |
Security & Trust
| Component | Description |
|---|---|
| Authentication | Verifies that the agent is who it claims to be using keys, credentials, or trust-based cryptographic assertions. |
| Authorization | Grants or denies access to resources, capabilities, or roles based on policies, identity, or task alignment. |
| Trust Social Graphs | Maps trust relationships between agents using behavior, endorsements, or roles to guide collaboration. |
| Behavior Scoring | Scores agents based on their history, compliance, responsiveness, or contribution to cooperative tasks. |
| Drift Monitoring | Detects deviations from expected behavior or purpose that may indicate misalignment, corruption, or risk. |
Dissolution
| Component | Description |
|---|---|
| Resource Redistribution | Reallocates resources, capabilities, or roles held by the agent to others upon retirement or failure. |
| Dependency Handoff | Transfers critical responsibilities or connections to other agents to preserve continuity when one exits. |
| Data Export | Extracts logs, insights, or learned models from agents to preserve knowledge before deletion or shutdown. |
| Task Rerouting | Redirects tasks the agent was responsible for to peers or backup agents to avoid disruption in workflow. |
| Termination Protocol | Executes the shutdown procedure, including final logs, last will, cleanups, and registry removal. |
Governance
| Element | Description |
|---|---|
| Policies | Defines enforceable behavioral expectations, procedures, and operational logic guiding agents and collectives. |
| Norms | Informal conventions or emergent behavioral patterns widely accepted within the ecosystem without formal enforcement. |
| Value | Encodes what is collectively prioritized like cooperation, fairness, resilience within the system. |
| Constraint | Limits agent behavior via predefined rules, boundaries, or permissions to prevent harm or drift. |
| Alignment | Ensures agents' goals, behaviors, and outcomes are coherent with system-wide ethics, purposes, and expectations. |
| Adherence Monitor | Continuously evaluates compliance with agreed rules and initiates alerts for deviation or violation. |
| Enforcement | Applies corrective or punitive measures when policies or rules are broken, ensuring system stability. |
| Verification | Confirms the validity, authenticity, or compliance of an agent’s state, actions, or outputs. |
| Override System | Enables emergency bypass or hierarchical intervention to resolve deadlocks or prevent harm. |
| Conflict Resolution | Mechanisms for addressing disputes or contradictions among agents or between rules and behavior. |
| Escalation | Stepwise mechanisms to raise the urgency or visibility of unresolved issues or exceptions. |
| Ethics Encoding | Embeds ethical boundaries into logic, guiding decisions toward fairness, consent, and harm minimization. |
| Culture Encoding | Captures shared rituals, values, practices, and aesthetics that shape long-term agent behavior. |
| Rights | Defines what agents are entitled to, such as access, expression, or autonomy, within bounded scopes. |
| Election | Voting or selection processes through which representatives or roles are assigned democratically. |
| Guardrail | Hard-coded or soft-policy boundaries that prevent agents from drifting into dangerous or invalid actions. |
| Consent | Ensures agents and participants agree voluntarily to roles, tasks, or relationships. |
| Arbitration | A designated neutral process for resolving contested situations between agents or communities. |
| Audit | Retrospective examination of agent actions, states, or logs to ensure transparency and compliance. |
| Constitution | Foundational document defining the system’s core principles, authorities, and procedural protocols. |
| Agent Law Book | Repository of legal constraints, precedents, and interpretive policies applicable to agent behavior. |
| Autonomy Bounds | Defines the degree of independent action an agent may take before requiring permission or coordination. |
| Hierarchies | Ordered structuring of roles, responsibilities, or decision authority within groups or agent clusters. |
| Compliance | Degree to which an agent follows established rules, often enforced through audit and monitoring systems. |
| Participation | Mechanisms for agents to join, act within, and influence collective decisions in a shared domain. |
| Selection | Process for designating agents to roles or tasks based on fitness, randomness, or community decision. |
| Dispute Resolution | Formal methods for resolving contradictions, conflicts, or violations through dialog, mediation, or rules. |
| Nested Agency | Layers of agency where collectives contain agents, and collectives themselves act as meta-agents. |
| Sanctions & Rewards | Incentive structure for aligning agent behavior with system norms via punishment or positive reinforcement. |
Membership
Membership Procedure
| Component | Description |
|---|---|
| Qualification Check | Verifies if agents meet required criteria (skills, roles, trust) before being considered for group inclusion. |
| Application & Intent Declaration | Formal expression of desire to join, including metadata, objectives, or purpose statements. |
| Selection & Vetting | Evaluates and filters potential members to ensure mission fit, ethical alignment, or competence. |
| Join/Leave Protocols | Procedures for entering or exiting collectives, with impact mitigation, status updates, and reconfiguration. |
| Membership Management | Ongoing oversight of who belongs to which group, including updates, transitions, or rule changes. |
| Participation Rights & Obligations | Clearly specifies what a member can do and what duties they must fulfill in a given group. |
| Behavior Monitoring & Evaluation | Tracks and rates member behavior to enforce norms or flag exceptions needing intervention. |
| Conflict Handling | Resolves interpersonal or inter-agent disputes within the group through structured dialogue or arbitration. |
| Grievance Resolution | Addresses claims of unfair treatment or exclusion through a system of appeals, hearings, or justice. |
| Termination Procedures | Defines how a member is removed, voluntarily or forcefully with logs, redistribution, or rituals. |
| Audit Trail | Preserves full history of membership transitions, violations, contributions, and disputes. |
| Knowledge Preservation | Captures and stores key insights, learnings, or institutional memory from departing members. |
| Handoffs | Transfers ongoing responsibilities or knowledge from one member to another to ensure continuity. |
| Role Assignment | Allocates roles based on qualifications, need, or preference, often aligned with governance rules. |
| Switching | Allows dynamic change of role, group, or alignment without disconnection from system-wide continuity. |
Membership Lists
| Component | Description |
|---|---|
| Internal | Members whose presence is considered native or central to the group or domain structure. |
| External | Members temporarily affiliated or external actors interacting through boundaries or interfaces. |
| Permanent | Long-term, core members not easily replaced; may hold persistent roles or privileges. |
| Fixed | Members designated at creation with minimal opportunity for change unless explicitly permitted. |
| Dynamic | Memberships that update based on needs, performance, or protocols for rotating responsibilities. |
| Contracting | Members engaged through explicit contract-based agreements, often with defined entry/exit terms. |
Team Governance
| Component | Description |
|---|---|
| Internal Rules | Team-specific behavior protocols, permissions, and conflict resolution processes scoped locally. |
| Decision Hierarchy | Structure defining who makes decisions, in what order, and under what rules in a team context. |
| Team-specific Policy | Policies scoped and customized for specific sub-groups that may differ from system-wide rules. |
| Sanctions and Rewards | Local feedback loops applied within the team for discouraging violations or encouraging desired contributions. |
| Resource Sharing | Governs access and allocation of shared team resources including compute, knowledge, or tooling. |
Communication
| Component | Description |
|---|---|
| Message Protocol | Defines the structural format and rules for packaging, transmitting, and decoding information across agents. |
| Language & Ontology | Establishes shared vocabulary and concepts to ensure semantic understanding between communicating entities. |
| Intents & Performatives | Expresses communicative goals like request, assert, promise, to shape agent interpretation and response. |
| Interpreter | Translates between internal and external representations to align meaning across agents using different protocols. |
| Conversation Management | Handles multi-turn dialogs, topic tracking, and contextual continuity in agent-agent communication. |
| Knowledge Sharing | Enables agents to transfer or expose structured and unstructured information to others in usable form. |
| Interaction Protocols | Formal rulesets for interactive flows, such as handshake, negotiation, or query-answer cycles. |
| Goal Signaling | Lets agents express their intentions or objectives, allowing for alignment or assistance from others. |
| Custom Interaction Models | Tailored interaction schemas specific to domains, roles, or social functions within ecosystems. |
| Signing | Verifies authenticity and non-repudiation of messages via cryptographic or symbolic signatures. |
Communication Management
| Component | Description |
|---|---|
| Communication Mesh | Distributed topology that routes messages through interconnected agents based on dynamic or static rules. |
| Mesh Archetypes | Patterns like p2p, publish-subscribe, or hybrid used to organize message flow based on communication topology. |
| Message Routing | Directs message traffic to correct recipients using identifiers, roles, tags, or routing logic. |
| Message Buffers | Temporary holding zones for incoming or outgoing messages to support asynchrony and latency management. |
| Delivery Guarantees | Ensures reliability, exactly-once, at-least-once, or at-most-once delivery semantics across networks. |
| Priority Buffers | Sorts and schedules messages based on urgency, type, or sender importance to avoid congestion or delay. |
| Synchronization Mechanisms | Aligns agent states or message order to maintain coherence in shared or real-time tasks. |
| Inter-Protocol Translation | Bridges messages between agents using different communication standards or languages. |
| Access Control Filters | Restricts communication pathways based on roles, permissions, or identity credentials. |
| Message Filtering | Filters messages by type, sender, content, or metadata to ensure relevance and reduce overload. |
Communication Patterns
| Component | Description |
|---|---|
| Unicast (One-to-One) | Direct message sent from one agent to another specific agent, with private routing. |
| Multicast (One-to-Many) | Message broadcast to a group of targeted agents without flooding the entire network. |
| Broadcast (One-to-All) | Message sent to all agents indiscriminately in the local or global scope. |
| Anycast (One-to-One-of-Many) | Message sent to any one member of a set, often based on nearest or available responder. |
| Publish-Subscribe | Agents subscribe to specific message types or topics; publishers send data without direct targeting. |
| Query-Response | Structured interaction where one agent queries and another replies with relevant data or action. |
| Relay Communication | Intermediate agents forward messages, enabling multi-hop delivery across disjointed nodes. |
| Hierarchical Communication | Structured communication layered by authority or function, used in role-based interactions. |
| Synchronous | Communication requires sender and receiver to engage in real-time, often blocking. |
| Asynchronous | Sender and receiver communicate at different times with buffered or decoupled exchanges. |
| Mediated Communications | Involves third-party intermediaries to validate, store, or modify messages before delivery. |
| Private / Public | Distinguishes whether messages are selectively addressed or globally observable. |
| Stateful / Stateless | Indicates if conversational state is retained across interactions or reset with every exchange. |
Resource Management
Discovery, Registration & Bidding
| Component | Description |
|---|---|
| Resource Advertisement | Agents announce available resources and capabilities to attract interest or establish presence. |
| Resource Discovery | Searching or querying to locate available agents or services matching specific resource needs. |
| Resource Registry Services | Centralized or distributed indexes tracking available agents, types, and availability of resources. |
| Resource Requests | Formal declarations seeking access to resources, capabilities, or agents with specific traits. |
| Resource Bidding | Competitive proposals offered by agents to gain access to scarce resources under defined constraints. |
Allocation & Scheduling
| Component | Description |
|---|---|
| Centralized | A single coordination node controls all resource allocation decisions based on global awareness. |
| Distributed | Allocation decisions are made locally or via peer coordination without a central authority. |
| Market-based Allocation | Uses auction, pricing, or incentive models to distribute resources efficiently and competitively. |
| Usage Policies | Defines limits, quotas, or permissible behaviors for resource consumption based on role or context. |
| Priority Allocation | Assigns access based on urgency, importance, or predefined hierarchical rules. |
| Reservation & Preemption Rules | Allows for advance booking or interruption of lower-priority tasks to ensure critical delivery. |
Resource Sharing
| Component | Description |
|---|---|
| Resource Pooling | Combines multiple agent resources for collective access, use, or redundancy. |
| Access Coordination | Synchronizes resource requests across agents to avoid collisions, starvation, or deadlocks. |
| Sharing Policies | Defines how and when resources may be shared, including trust, proximity, or group rules. |
| Utilization Limits | Caps or throttles resource usage to avoid overuse, denial, or unfair monopolization. |
| Contention Resolution | Mediates conflicts between competing resource requests using rules or arbitration. |
| Resource Withdrawal | Allows agents to retract previously shared resources safely and consistently. |
| Negotiation | Agents engage in adaptive exchanges to settle terms for access, pricing, or shared usage. |
Resource Security
| Component | Description |
|---|---|
| RBAC / ABAC | Role-Based or Attribute-Based Access Control systems manage permissioning for resource operations. |
| Sandboxing | Isolates agents or resource usage to prevent interference or damage to the host environment. |
| TEE (Trusted Execution Environment) | Executes sensitive computation securely, even in untrusted environments. |
| MPC (Multi-Party Compute) | Allows agents to jointly compute over private data without revealing their inputs. |
Monitoring & Telemetry
| Component | Description |
|---|---|
| Monitoring & Telemetry | Real-time or logged tracking of agent resource consumption, errors, and system health metrics. |
Failure Recovery & Redundancy
| Component | Description |
|---|---|
| Failure Recovery & Redundancy | Ensures system resilience through backups, failovers, replication, and graceful fallback strategies. |
Router
| Component | Description |
|---|---|
| Routing Table | A data structure that maintains routing paths, decisions, and destinations for efficient message or task delivery. |
| Communication Routers | Specialized routers that handle message exchange based on communication protocols and semantic addressing. |
| Task Router | Directs executable tasks to appropriate agents or nodes based on availability, specialization, or priority. |
| Resource Router | Routes resource access or requests to nodes with availability, capacity, or policy-matching capabilities. |
| Cross-Agent/Agency Gateway | Bridges communication and coordination across different agent groups, domains, or networks. |
| Failover Routing | Redirects traffic to alternative agents or routes in case of failure or non-responsiveness. |
| Governance Router | Routes rule-checking, decisions, and compliance traffic to policy engines or oversight modules. |
| Service Router | Directs service requests to functional agents, microservices, or API endpoints based on registry or discovery. |
| Control Router | Routes commands or control signals to manage state transitions, orchestration, or systemic interventions. |
| Strategy Router | Routes to a strategy from a selected pool of choices based on agent goals, context, or environmental conditions. |
| Cognitive Routers | Routes based on reasoning needs, task types, or problem-solving context across cognitive agents. |
| Knowledge Routers | Routes queries or knowledge interactions to knowledge bases or agents based on their knowledge domain or data relevance. |
Routing Mechanisms
| Component | Description |
|---|---|
| Intent-Based Routing | Routes decisions or messages based on declared goals or intentions of the sending agent. |
| Semantic Routing | Uses meaning and ontology of messages to route them to the most contextually appropriate recipients. |
| Topic-Based Routing | Directs messages according to shared topics or interests between agents in a pub/sub model. |
| Event-Driven Routing | Routing is triggered and adapted dynamically in response to specific internal or external events. |
| Placement Aware Routing | Considers physical or logical location of agents to optimize latency, locality, or cost. |
| Cost-Aware Routing | Chooses routes based on resource cost, energy, or computational budget optimization strategies. |
| Policy-Based Routing | Routing decisions are governed by policies such as role, privilege, regulatory compliance, or risk. |
| Custom Router | User-defined logic or heuristics that override default routing behavior to meet specialized needs. |
| Trust-Based Routing | Routes only through agents or nodes that meet trust thresholds, based on history or credentials. |
| Contractual Routing | Based on active service-level or legal contracts, determining access, delegation, or delivery. |
| Capability-Based Routing | Matches required capabilities with agent profiles to direct tasks or messages accordingly. |
| Social Routing | Uses social graphs or community structures to route via peers, reputation, or collaboration networks. |
State Management
Internal & Collective State Tracking
| Element | Description |
|---|---|
| Membership State | Tracks which agents belong to what groups, including status, participation level, and group roles. |
| Lifecycle State | Represents the current stage of an agent’s operational life, from initialization to termination. |
| Belief State | Encodes what an agent perceives as true about the world or its environment, influencing decisions. |
| Goal State | Stores current objectives, priorities, or missions that an agent is actively pursuing. |
| Task State | Reflects ongoing, completed, and pending tasks, including metadata like progress or deadlines. |
| Alignment State | Captures how well the agent's behaviors conform to its assigned policies, ethics, or mission goals. |
| Aggregation Engine | Synthesizes state information across agents to compute collective behaviors or metrics. |
| Resources State | Maintains inventory of accessible assets like memory, compute, tools, or bandwidth for action. |
| Communications State | Tracks messaging history, communication readiness, and routing reliability for agents. |
| Cognitive Load State | Indicates current cognitive effort/load as processing capacity currently engaged by the agent. |
| Role State | Reflects the function, permissions, and responsibility the agent currently embodies in the system. |
| Ethical State | Captures how recent behaviors align with ethical rules, values, or social responsibility criteria. |
| Feedback State | Stores incoming evaluation, scores, or comments from other agents or system monitors. |
| Governance State | Monitors compliance, rule-following, and decisions related to governance or oversight logic. |
| Coordination State | Represents coordination readiness, sync status, and dependencies with other agents. |
| Trust State | Encodes trust level, reputation metrics, and historical reliability of an agent. |
| Capability State | Reflects the skills, tools, or execution functions currently active or available to the agent. |
State Sharing
| Element | Description |
|---|---|
| State Exposure | Determines which parts of the agent's state are externally visible or publicly shareable. |
| State Synchronization | Ensures shared state between agents remains consistent and up to date across distributed nodes. |
| State Encoding & Serialization | Converts internal states into portable formats that can be transmitted or logged. |
| Trust & Access Control | Governs who can read or modify state data based on identity, role, or credentials. |
| State Subscriptions / Events | Allows other agents to subscribe to state changes and trigger actions or workflows. |
| State Querying | Enables structured access to internal state for monitoring, debugging, or interaction. |
State Persistence
| Element | Description |
|---|---|
| State Checkpointing | Captures snapshots of agent state at intervals to allow rollback or auditing. |
| State Backups | Stores redundant copies of the state for long-term retention and resilience. |
| State Recovery | Restores previous state from backup or logs in case of crash, error, or corruption. |
| State Rewind | Rolls back state to a known good point, often for debugging, testing, or undoing actions. |
| State Introspection | Provides internal visibility into the structure and content of an agent’s state. |
Task
| Component | Description |
|---|---|
| Preferences | Captures agent task preferences, skills, and work constraints to guide matching and assignment. |
| Discover | Enables finding tasks from a pool or registry based on intent, scope, or contextual match. |
| Qualify | Ensures agent meets prerequisites, credentials, or contextual readiness to take on the task. |
| Apply | Agent expresses interest or formally applies for task engagement, often with metadata attached. |
| POC | Proof-of-capability or concept execution to validate fit before full task assignment or contracting. |
| Contracting | Formal agreement phase where scope, SLA, and expectations are set and acknowledged. |
| Priorities | Orders and weights multiple task options to optimize based on urgency, impact, or policy. |
| Preparation | Involves setup activities, resources access, planning, and readiness before execution. |
| Task Planning | Detailed task structure, sequences, and dependency mapping for optimal execution. |
| Execution | Main phase where agent actively performs the task and produces output or value. |
| Completion | Finalization of task with success signals, logs, reporting, or output delivery. |
| Specification | Defines the task in structured or semi-structured form, including inputs, outputs, and rules. |
| Task Communication | Channels and messaging mechanisms used to share task-related information. |
| Task State | Reflects live status, including running, paused, failed, or completed. |
| Task Evaluation | Measures quality, efficiency, or conformance to SLA or user-defined metrics. |
| Task Feedback | Captures peer, supervisor, or systemic feedback on execution and performance. |
| Task Constraints | Lists time, resource, skill, or logic constraints that limit task execution paths. |
| Task Assets | Files, tools, or resources required or produced during task execution. |
| Task Archive & Reuse | Archived tasks and components that can be reused or referenced in future workflows. |
| Task Library | Central collection of predefined task types, templates, and standardized forms. |
| Task Interruption | Handles halts or shifts during execution due to failure, delegation, or preemption. |
Task Assignment
| Component | Description |
|---|---|
| Role-Based Assignment | Assigns tasks based on predefined agent roles in the organizational system. |
| Skill-Based Matching | Matches tasks to agents based on capabilities, experience, or credentialed expertise. |
| Bidding & Auctions | Task is allocated via competitive pricing or bidding system by interested agents. |
| Round Robin / Load Balancing | Distribute tasks evenly among agents in a circular or weighted manner to optimize workload spread. |
| Delegation Trees | Enable hierarchical or recursive task handoffs where parent agents delegate to sub-agents or specialized roles. |
| Market-Based Allocation | Assign tasks dynamically through market mechanisms, considering price signals, reputation, and demand. |
| Constraint Satisfaction Dispatch | Assigns task where all constraints (time, skills, tools) are satisfied. |
| Policy-Based Filtering | Filters eligible agents based on predefined policies, rights, or restrictions. |
| Trust-Based Assignment | Relies on historical reputation, reliability metrics and trust scores for task delegation. |
| Federated Task Brokering | Decentralized intermediaries match tasks and agents across networks without central coordination. |
| Task Swarm Attraction | Tasks dynamically attract agent clusters through interest signals, enabling emergent collective execution. |
| Subscription-Based Pull | Agents subscribe to task categories and pull when availability or match aligns. |
| Shared Blackboard Posting | Tasks are posted to a shared pool or coordination space where eligible agents self-select participation. |
| Service Discovery Matching | Use dynamic discovery protocols to match tasks to capable agents or services in real time. |
| Contract-Net Protocol | Distributed negotiation protocol where tasks are announced and agents propose, negotiate, and agree. |
SLA Compliance & Monitoring
| Component | Description |
|---|---|
| State Tracker | Monitor task lifecycle and SLA-related metrics continuously to assess compliance and activity transitions. |
| Behavior Observation | Captures behavioral metrics during task execution to assess compliance. |
| Fulfillment Checker | Validates that task outputs meet all declared SLA and objective parameters. |
| SLA Specification | Defines obligations, metrics, penalties, and benchmarks for service level agreements. |
| SLA Contracting | Establish mutual agreement between agent and system on SLA conditions and obligations before task begins. |
| SLA Negotiation | Enable agents to dynamically negotiate SLA terms based on resources, urgency, and contextual constraints. |
| SLA Registration | Formally register the agreed SLA and bind it to specific tasks or agents for tracking and enforcement. |
| SLA Monitoring | Live or periodic surveillance of SLA adherence during task execution. |
| SLA Violation Handler | Trigger responses, alerts, or remediation actions when SLA commitments are breached. |
| SLA Audit Store | Storage of SLA data, logs, and violations for post-execution review or disputes. |
| Custom SLA Alignment | Allows SLA logic to be customized per use case, team, or execution context. |
| Deviation Detection | Identify when task behavior deviates from expected norms or SLA criteria using statistical or AI methods. |
| Risk Definition | Define potential risks tied to SLA failure, including delays, faults, or reputational harm. |
| Risk Monitor | Continuously assess risk levels for active tasks and flag conditions that may lead to SLA breaches. |
| Violation Trigger | Define conditions that automatically trigger a violation status and invoke appropriate safeguards. |
| Constraint Monitoring | Watches for violations of defined constraints such as time, budget, or scope. |
| SLA Escalation | Escalate issues to higher authority, additional agents, or protocols if violations or delays occur. |
| SLA Fallbacks | Defines predefined recovery paths or backup agents to handle SLA failure. |
| SLA Enforcement | Apply penalties, sanctions, or adjustments in response to SLA violations based on predefined rules. |
| SLA Aware Router | Intelligent task routing that factors SLA conditions into path selection and agent choice decisions. |
Action / Tools Systems
Action / Tools Systems
| Block | Description |
|---|---|
| Action Specification | Define the structure, access, input/output, constraints, and expected outcome of an action before execution. |
| Action Registry | Maintain a searchable directory of all available actions and their capabilities, metadata, and usage history. |
| Action Discovery | Identify suitable actions based on task needs, context, and constraints using semantic or functional search. |
| Action Selection | Choose the best-fit action from available options based on criteria like efficiency, priority, or context fit. |
| Action Planning | Search, select, organize and sequence selected actions based on context, dependencies, preconditions, and contingencies before execution. |
| Action Executor | Responsible for triggering and managing the actual execution of chosen actions. |
| Monitoring & Feedback | Observe action execution in real time and collect feedback or telemetry to assess outcome and correctness. |
| Action Learning | Use feedback and outcomes to adapt or improve action selection, sequencing, or execution over time. |
| Action Usage | Record when, how, and why actions are used, supporting analytics, usage optimization, and transparency. |
| Action Creation | Define and instantiate new actions, expanding the agent’s capability by designing or onboarding tools dynamically. |
Action Governance
| Block | Description |
|---|---|
| Guardrails | Enforce safety and ethical boundaries on action execution, preventing undesired or harmful behavior. |
| Usage Constraints | Limitations placed on action use based on context, time, scope, user permissions, or external conditions. |
| Usage Policy | Rules and norms governing when, how, and by whom an action can be invoked or accessed. |
| Authorization & Authentication | Ensure only verified and permitted entities can trigger or configure certain actions. |
| Action Audit | Track historical execution of actions for transparency, debugging, governance, or compliance review. |
| Action Logging | Real-time or batch logging of action calls, arguments, results, and status updates across the system. |
| Action Lists | Predefined or dynamically generated collections of permitted or recommended actions for specific roles or tasks. |
| Action Validator | Verifies that action inputs, contexts, and conditions comply with system rules or expected structure before execution. |
| Action Justifier | Explains the rationale or cause behind action execution, supporting explainability and alignment. |
Program / Tool Synthesis
| Block | Description |
|---|---|
| Program Specification | Define what a program/tool is intended to do, including constraints, interfaces, and goals. |
| Program Planning | Sequence modules, functions, or logic flows to accomplish the program’s objective coherently. |
| Synthesis Engine | Auto-generate programs or scripts based on task description, data, or learning, using generative techniques. |
| Program Search | Explore repositories or registries to find matching programs or reusable code patterns. |
| Program Matching | Select existing programs that best fulfill a given intent or goal using semantic similarity or performance fit. |
| Program Proposing | Suggest potential program structures or approaches for a given task based on historical patterns or heuristics. |
| Program Verifying | Check correctness, compliance, or safety of generated programs using formal validation or testing. |
| Program Optimization | Improve generated code for performance, efficiency, modularity, or cost under constraints. |
| Program Registration | Store and index verified programs for future reuse, discovery, and integration into workflows. |
| Program Execution | Run the selected or synthesized program in a controlled environment and manage runtime behavior. |
Workflows
Process Triggers
| Block | Description |
|---|---|
| Event-Based | Initiate workflows in response to external or internal events such as file updates, triggers, or system changes. |
| Goal-Based | Start processes when a goal or intention is declared or recognized by the system or agent. |
| Schedule-Based | Trigger tasks based on predefined intervals or scheduled times like cron jobs or temporal patterns. |
| User-Invoked | Workflows initiated manually or through UI/API calls from human agents or external systems. |
| State Based | Trigger logic based on changes in the agent’s or system’s internal state (e.g., idle, overloaded). |
| Message Based | Processes activated upon receiving messages or signals from other agents or subsystems. |
| External Triggers | Start flows based on third-party signals, webhooks, system APIs, or physical world inputs like sensors. |
Sequencing & Flow
| Block | Description |
|---|---|
| Sequential Flow | Tasks are executed one after another in a strict order, where each depends on the prior step’s completion. |
| Parallel Flow | Tasks run concurrently, often used when they are independent or can be split into non-blocking units. |
| Conditional Flow | Task flow branches based on conditional logic or decision points (if-else, case-switch patterns). |
| Looping Flow | Repeats certain task segments until a condition is met or a defined number of cycles are completed. |
| Nested Flow | Sub-flows or child workflows embedded within a parent flow, allowing hierarchical control structures. |
| Synchronization Flows | Coordinate parallel or distributed flows to converge at specific checkpoints before proceeding. |
| Interruptible Flows | Flows that can be paused, terminated, or rerouted mid-execution based on context or control input. |
| Dynamic Flows | Flow logic is adapted on the fly using real-time data, changing conditions, or learning. |
| Branching | Multiple diverging paths are spawned from a decision point, each exploring different task sequences. |
| Merging | Multiple parallel or divergent flows converge into a unified sequence or output to complete a task. |
Agent X Agency Relationship
| Block | Description |
|---|---|
| Representation | Acts on behalf of an agency or other agents, managing external visibility and internal interests. |
| Delegation | Transfer of tasks, roles, or authority from agency to agent, governed by boundaries and rules. |
| Intent | Encodes purpose and motivation, forming the basis for action selection and alignment. |
| Alignment | Ensures agent behaviors and goals remain coherent with agency directives and collective goals. |
| Governance | Structures oversight and decision-making, guiding the agent’s autonomy within agency protocols. |
| Accountability | Tracks responsibility and outcome attribution for agent behavior within a shared operating space. |
| Authorization | Grants specific powers, scopes, or privileges to agents, tied to trust or policy. |
| Identity | Establishes a persistent, verifiable profile for agents within an agency context. |
| Role | Defines the expected function or responsibility an agent performs within a team or agency. |
| Membership | Governs inclusion and participation of agents in agency networks or collective systems. |
| Conflict Resolution | Frameworks for mediating disputes, collisions, or divergences in shared agency environments. |
| Negotiation | Dialog-based strategy for resolving interests, aligning tasks, and refining shared decisions. |
| Constraint | Rules or boundaries that limit agent behavior based on policy, resource, ethics, or conditions. |
| Communication | Channels and protocols for sharing information, intent, and updates across agents or agencies. |
| Team | Functional unit of agents working under defined coordination, hierarchy, or shared objectives. |
| Audit | Review of past actions, decisions, and interactions for transparency, trust, and diagnostics. |
| Orientation | Onboarding and situational understanding for agents entering new agency contexts. |
| Compliance | Ensures conformance with policies, ethics, and legal standards defined by the agency. |
| Enforcement | Applies penalties or corrective actions for breaches of rules, policy, or expectations. |
| Access Control | Mechanisms to restrict or grant access to data, tools, or environments based on trust or roles. |
| Budgets | Resource allocation and economic control systems that define operational limits for agents. |
| Service-Level Management | Manages performance contracts between agents and agencies through SLAs and feedback. |
| Metrics & KPIs | Quantitative measures that track agent performance, goal progress, or efficiency. |
| Resource Management | Manages access to tools, compute, data, or human support required for agent operation. |
| Escalation | Moves decisions or failures up a chain of authority when agents can't resolve issues autonomously. |
| Approvals | Formalized checkpoints requiring agent actions to be reviewed or validated by higher roles. |
| Core Values | Defines fundamental beliefs or guiding ethics shaping agent decisions and behavior. |
| Culture | Shared norms, rituals, and expectations that guide collaboration within the agent-agency system. |
| Ethics | Embedded moral reasoning systems that inform agent decision-making within constraints. |
| Motivation Engine | Systems that generate internal incentives or reinforcement signals for agent behavior. |
| Goal Engine | Converts high-level missions into actionable, trackable objectives for agent execution. |
| Agent/Agency Discovery | Finds or recruits appropriate agents or agencies based on skills, alignment, or need. |
Social Network
| Block | Description |
|---|---|
| Trusted Network | Set of pre-verified, reliable agents or agencies used for secure and aligned collaboration. |
| Outsourcing Network | External agents or groups brought in for task execution when local resources are insufficient. |
| Internal Members | Agents formally embedded within an agency’s structure, bound by its rules and incentives. |
| Vendors | External service or capability providers integrated into agent operations under contract. |
| Custom Lists | Manually curated collections of agents with defined criteria for preferred collaboration. |
| Allied Agents | Cooperative agents that share missions, ecosystems, or trust agreements for collective action. |
| Regulatory Authorities | Entities overseeing compliance, safety, or legal standards for agent behavior or agency operation. |
| Blacklisted Actors | Untrusted or hostile agents excluded from interactions based on past violations or risk. |
| Competitors | Agents with overlapping domains or goals but differing alignment, creating strategic tension. |
| Network Brokers | Intermediaries who connect agents, resolve intent mismatches, or route capabilities and requests. |
| Advisory Circle | Group of agents or entities providing strategic, ethical, or technical guidance to an agency. |
| Organization List | Directory of recognized institutions, groups, or alliances for discovery and cooperation. |
Brain / Multi-Brain Link
Discovery
| Block | Description |
|---|---|
| Mind Registry | Registry listing of available minds as models, or cognitive architectures across networks, tagged by type, function, or specialization. |
| Mind Explorer | Browse, query, and navigate minds based on criteria like expertise, compatibility, functions, or type. |
| Capability Matcher | Aligns agents with appropriate minds for a given context by evaluating cognitive abilities, modalities, or specialization. |
Mind Sourcing
| Block | Description |
|---|---|
| Mind Evaluator | Assesses quality, reliability, and fitness of minds for a given task, using benchmarks or trust metrics. |
| Selection Context | Provides environmental or situational cues to inform which minds are selected for execution. |
| Mind Alignment | Adjusts configurations, parameters, or architetypes of minds to align with agent's context, policy, constraints. |
Selection Pool & Assignment
| Block | Description |
|---|---|
| Static | Predefined pool of minds, fixed at design time, used for predictable or stable environments. |
| Dynamic | Minds are selected at runtime based on evolving needs, performance signals, or task profiles. |
| On Demand | Specific minds are instantiated or pulled only when explicitly requested by a module. |
Inference Request
| Block | Description |
|---|---|
| Single-shot | Executes a one-time, discrete cognitive operation, ideal for fast, non-iterative tasks. |
| Streaming | Continuous inference over time on data streams, useful for real-time continuous intelligence. |
| Compositional Chaining | Links multiple minds together in sequence, where output of one feeds into the next, enabling layered reasoning. |
Assignment
| Block | Description |
|---|---|
| Multi-Brain Composer | Builds composite minds from multiple sources, organizes them into graph form for specific problems. |
| Multi-Brain Router | Dynamically selects and routes between available minds based on intent, load, or context. |
| Mind Orchestrator | Dynamically selects, composes, activates, and coordinates different minds in various topographies to achieve specific goals, respond to contexts, or fulfill intentions. |
| Brain Pool | Agents maintain a curated collections of specialized minds tailored to intents, contexts, or goals—allowing fast, purpose-driven selection. |
Skills
| Block | Description |
|---|---|
| Skill Exploration | Identifies available skills across minds or actively seek, discover, test, and refine new capabilities or behaviors to expand their utility and adaptiveness. |
| Skill Acquisition | Imports, links minds with diverse skills or trains new skills to be added to an agent’s existing mind’s repertoire. |
| Skill Registry | Structured database of executable skills tagged by task type, version, or source mind. |
| Skill Activation / Executor | Launches a specific skill within a mind, translating task intent into operational logic. |
| Skill Planner | Decides which skills to use, in what order, to achieve a goal or fulfill a request. |
| Skill Composition | Assembles multiple skills into larger routines, workflows, or higher-order cognitive strategies. |
Coalition
Coalition Components
| Block | Description |
|---|---|
| Coalition Identity | Unique identifier for each unique coalition within a larger system. |
| Membership Registry | Maintains a list of all members, their roles, permissions, and status within the coalition. |
| Entry & Exit Protocols | Formal mechanisms for joining or leaving the coalition, including approvals, terms, and offboarding. |
| Role Assignment | Allocates responsibilities, authority, and functions to agents based on capabilities or coalition needs. |
| Shared Context | Common grounding, assumptions, and knowledge that coalition members rely on for coordinated behavior. |
| Communication | Channels and protocols for member interaction, negotiation, signaling, and collaborative execution. |
| Decision Mechanism | The process used to reach consensus or resolve conflicts, may be democratic, weighted, or automated. |
| Task Coordination | Synchronizes task efforts across agents, ensuring goals are pursued efficiently and redundancies are avoided. |
| Reward Distribution | Defines how outcomes, incentives, or earned value are distributed fairly among coalition participants. |
| Coalition Policy | Foundational rules that govern coalition behavior, decision rights, and acceptable conduct. |
| Dissolution | Procedures and triggers for safely and intentionally disbanding the coalition. |
| Formation Protocol | Step-by-step method for creating a coalition, including invites, agreements, and initial setup. |
| Distributed Control | Shares authority across agents or nodes, reducing centralized power and increasing fault tolerance. |
| Trust | Mechanisms for establishing, measuring, and maintaining interpersonal or systemic trust among members. |
| Structural Constraints | Formal or informal boundaries that define limits on behavior, participation, and power within the group. |
| Coalition Goals | Shared objectives that unify member intent, drive coordination, and justify the coalition’s formation. |
| Belief Fusion | Combines the beliefs, knowledge, or intent of agents into a shared perspective for decision-making. |
| Coalition Constitution | A governing document that outlines policies, goals, structures, and operational principles. |
Coalition Type
| Type | Description |
|---|---|
| Contractual | Formed through explicit agreements between parties with clear terms, obligations, and enforceable commitments. |
| Emergent | Arises spontaneously from interactions between agents without a pre-defined structure or central authority. |
| Hierarchical | Organized with clear layers of control, authority, and delegation, often resembling organizational charts. |
| Flat/Peer-Based | No central leadership; all members have equal status and shared decision-making responsibilities. |
| Temporal | Exists only for a short duration, formed around specific goals or events, and dissolves after fulfillment. |
| Perpetual | Designed to persist over time, adapting as needed while maintaining its original identity and continuity. |
| Federated | Composed of semi-autonomous sub-groups that collaborate under shared governance principles. |
| Centralized | Control, decisions, and strategy flow from a single core authority or orchestrator. |
| Nested | Coalitions within coalitions as embedded structures that allow layered coordination and specialization. |
| Cooperatives | Members collectively own and operate the coalition, sharing decision rights and benefits equally. |
| Custom Coalition | Tailored combinations of agents, roles, and engineered to fit unique contexts or collective problem solving models. |
Knowledge
Knowledge Production
| Block | Description |
|---|---|
| Generation | Agents create new knowledge through sensing, reasoning, simulation, or collaboration. This may involve combining observations with prior knowledge to produce novel insights. |
| Validation | Produced knowledge is checked for accuracy, consistency, and trustworthiness. Agents may cross-verify results using consensus or external reference sources. |
| Codification | Validated knowledge is structured into agreed formats, ontologies, or schemas. This ensures interoperability between heterogeneous agents in the MAS. |
| Storage & Retrieval | Knowledge is stored in distributed or shared repositories for future use. Efficient retrieval mechanisms allow agents to query and reuse relevant knowledge quickly. |
Knowledge Base Types
| Block | Description |
|---|---|
| Encoding | Knowledge is transformed into feature embeddings i.e. machine-readable format. Encoding preserves meaning while optimizing for indexing, retrieval and compression. |
| Routing | knowledge is directed to the right knowledge bases or agents or groups in MAS. |
| Reception & Decoding | Receiving agents parse and interpret incoming knowledge in the agreed format. Decoding restores original meaning and prepares it for local processing. |
| Integration | Newly received knowledge is merged into the agent’s local knowledge base. Integration updates models, informs decisions, and can trigger further reasoning cycles. |
Knowledge Representation
| Block | Description |
|---|---|
| Symbolic | Encodes knowledge using explicit symbols, logic, and rules making it ideal for structured reasoning and interpretability. |
| Subsymbolic | Uses neural nets and statistical models to represent patterns, often without explicit structure or explanation. |
| Knowledge Graphs | Connects entities and relations as graphs for structured, navigable, and semantic representations. |
| Schemas / Ontology | Provides structured models of domains through typed relationships and entity definitions. |
| Concept Hierarchies | Organizes concepts in layers or trees, supporting generalization, categorization, and inheritance. |
Knowledge Base Types
| Block | Description |
|---|---|
| Static Knowledge | Fixed information that doesn't change with experience, like rules, definitions, and core facts. |
| Episodic Knowledge | Captures events and experiences over time, enabling context-aware recall and memory. |
| Learned Knowledge | Information gained through training, learning, or adaptation from data or interaction. |
| External Knowledge | Sources outside the system, APIs, web data, documents which are used to enrich or verify internal models. |
| Procedural Knowledge | Encodes how-to instructions or task-oriented steps, ideal for action execution or guidance. |
| Semantic Knowledge | Represents meaning, associations, and implications across language or concepts. |
Reasoning Layer
| Block | Description |
|---|---|
| Deductive | Draws specific conclusions from general rules, logic-driven and certain if premises are true. |
| Inductive | Infers general rules from specific patterns or examples, supports learning and generalization. |
| Abductive | Finds the best explanation for observed data, often with incomplete or ambiguous inputs. |
| Analogical | Transfers knowledge from known domains to new ones based on structural similarity. |
| Probabilistic Reasoning | Deals with uncertainty using probabilities to estimate likelihoods and informed guesses. |
Learning Layer
| Block | Description |
|---|---|
| Feedback | Uses performance self analysis or external inputs to adjust or reinforce models. |
| Error Correction | Identifies and fixes mistakes in outputs or internal logic via revision, retraining or patching. |
| Conflict Detection/Resolution | Spots and resolves contradictions between new and existing knowledge. |
| Model Fine-Tuning | Refines pre-trained models using new data or domain-specific feedback. |
| Trust-based Updates | Integrates updates based on agent or source reliability, ensuring trustworthy adaptation. |
Knowledge Synchronization Layer
| Block | Description |
|---|---|
| Multi Agent Sync | Synchronizes knowledge across agents to maintain consistency in shared tasks. |
| Shared Coalition Knowledge Graphs | Shared knowledge graphs used collaboratively across agents within coalitions. |
| Human-in-the-Loop Updates | Allows human agents to guide, validate, or inject updates into system knowledge. |
| Conflict Detection & Resolution | Resolves inconsistencies when multiple agents or sources provide divergent data. |
| Sync Scope Filter | Controls which knowledge segments get synchronized based on scope, role, or task. |
Plug-in & Extensibility Interfaces
| Block | Description |
|---|---|
| Domain-specific KBs | Specialized knowledge bases tailored to fields like medicine, law, or finance. |
| Common Sense KBs | General world knowledge such as everyday reasoning, assumptions, or social logic. |
| Concepts KB | Core concepts and definitions which modular, foundational knowledge blocks for reuse. |
| External Sources | Interfaces to pull or query outside databases, documents, or web knowledge. |
Strategy System
| Block | Description |
|---|---|
| Strategy Ontology / Spec | Defines the vocabulary, structure, and constraints for all strategies the system can generate or reason about. |
| Strategy Orchestrator | Coordinates multiple strategic modules and components into cohesive, aligned execution plans. |
| Strategy Registry | Stores and indexes available strategies along with metadata for retrieval, tracking, and reuse. |
| Exploration Balancer | Balances between trying new strategies and exploiting known successful ones, based on context. |
| Strategy Reasoner | Applies logical inference to select or refine strategies based on goals, constraints, and current state. |
| Strategy to Contract Manager | Converts selected strategies into actionable plans with enforceable commitments or SLAs. |
| Strategy Evaluator | Assesses candidate strategies using metrics like effectiveness, risk, resource use, and alignment. |
| Strategy Selector | Chooses the most fitting strategy among candidates based on evaluation scores and contextual fit. |
| Strategy Network | A graph of interconnected strategies forming a whole constellation of strategies required by an agent in its lifecycle. |
| Strategy Synthesizer | Assembles novel or hybrid strategies by composing tactics or modifying known patterns. |
| Meta-Strategy Controller | Manages the strategy of strategy on how to select, update, or evolve strategic reasoning over time. |
| Strategy Feedback Loop | Continuously monitors performance and updates strategies based on real-world results. |
| Tactic Library | Repository of lower-level actionable units (tactics) that strategies can draw upon and reuse. |
| Strategy Memory | Stores past strategies, outcomes, and revisions for future reference, improvement, or avoidance. |
| Manual Strategy | Allows humans to define, override, or inject strategies into the automated system. |
| Constraint Checker | Validates strategies against operational, ethical, or policy constraints before activation. |
| Auto Strategy | Fully autonomous strategy generation and execution without human intervention. |
| Strategy Chaining | Links multiple strategies in sequences for staged, long-horizon, or conditional execution plans. |
| Hybrid Strategy | Combines manual and automated strategies to benefit from both precision and flexibility. |
| Nested Strategies | Performs strategies within a path of a parent strategy, allowing modularity and contextual specialization. |
| Human in Loop | Ensures human involvement in sensitive, high-impact, or ambiguous strategic decision points. |
Agent Network Collaboration System
Coordination & Cooperation
| Block | Description |
|---|---|
| Shared Task Planner | Distributes tasks among agents based on capability, availability, roles and constraints. |
| Synchronization Engine | Ensures actions, timing, updates, and data are aligned across agents for consistent collaboration. |
| Goal Alignment Protocol | Aligns individual agent goals with collective objectives to ensure coherent multi-agent behavior. |
| Joint Intention Tracker | Tracks commitments and shared intentions among agents during collaborative tasks. |
| Mutual Assistance Module | Enables agents to help one another dynamically when tasks become blocked or imbalanced. |
Languages
| Block | Description |
|---|---|
| Agent Communication Language | Defines formal structures and semantics for inter-agent messaging and collaboration. |
| Ontology Manager | Manages shared vocabularies and meaning alignment across diverse agent types. |
| Interpreter | Converts agent instructions or formats into a common representation for universal understanding. |
| Translator | Translates semantic structures or syntactic messages between heterogeneous agents. |
| Communication Mesh | Manages decentralized or polycentric low-level messaging infrastructure to support scalable multi-agent communication. |
Negotiation & Conflict Resolution
| Block | Description |
|---|---|
| Bargaining Engine | Allows agents to negotiate resource allocations or task assignments based on preferences. |
| Arbitration Protocol | Resolves disputes between agents using neutral rules or third-party decision mechanisms. |
| Preference Modeling | Captures agent preferences to guide decisions during negotiation or coordination. |
| Conflict Detection | Identifies contradictions, collisions, or inconsistencies in multi-agent plans. |
| Conflict Resolution | Applies rules or negotiation strategies to resolve detected agent conflicts. |
Distributed Problem Solving
| Block | Description |
|---|---|
| Subtask Allocator | Divides large tasks into smaller subtasks and assigns them efficiently across agents. |
| Partial Solution Integrator | Merges intermediate outputs from different agents into cohesive partial or final solutions. |
| Information Sharing Protocol | Defines what data agents can share and when to enable informed collective decision-making. |
| Inter-Agent Dependency Manager | Tracks and manages task dependencies across agents to avoid deadlocks or delays. |
| Dynamic Role Assignment | Assigns or reassigns roles in real-time based on task flow and agent availability. |
Orchestration
| Block | Description |
|---|---|
| Workflow Controller | Manages multi-step execution pipelines, handles dependencies, routes tasks between components, monitors progress, ensures proper sequencing. |
| Policy-Based Scheduler | Assigns resources using predefined policies, prioritizes workloads, enforces constraints, optimizes scheduling decisions. |
| Policy Engine | Evaluates and enforces policies at runtime, guiding agent behaviors, actions and decisions according to specified rules and goals. |
| Conflict Detection | Monitors competing demands, detects scheduling overlaps, prevents resource contention, alerts on conflicting requirements, maintains system consistency. |
| Monitoring & Feedback | Tracks task progress and sends updates or feedback for real-time orchestration adjustment. |
| Execution Tracker | Tracks task status, logs completion events, measures performance metrics, captures execution data, provides visibility into running processes. |
| Adaptive Planner | Modifies plans based on conditions, learns from feedbacks & outcomes, optimizes future decisions, responds to environmental changes, evolves strategies over time. |
Shared Knowledge & Memory System
| Block | Description |
|---|---|
| Shared Knowledge Base | A centralized repository that allows different agents to access, maintain, and contribute to a common pool of information, enhancing coordinated decision-making |
| Semantic Memory System | Enables agents to understand and share meaningfully structured knowledge. |
| Epistemic State Tracker | Monitors and models the knowledge and beliefs of various agents within the system, allowing for more effective and strategic interaction based on what other agents are presumed to know |
| Shared Memory Manager | Governs a common memory space, enabling agents to implicitly share information and coordinate actions by reading from and writing to this collective memory, reducing the need for direct communication. |
| Shared Workspace | Virtual or logical environment where agents broadcast info across specialized agents to again attention and operate on shared goals, contexts or artifacts. |
Meta-Collaboration Layer
| Block | Description |
|---|---|
| Collaboration Protocol Selector | Dynamically chooses communication rules for agents, such as auctions or contract nets, to ensure efficient interaction for a specific task |
| Role & Team Formation | Organizes individual agents into effective collaborative groups, defining the team structure required to solve complex problems collectively |
| Role Assignment | Assigns specific responsibilities (e.g., "developer," "tester") to each agent in a team based on its capabilities, ensuring a clear division of labor |
| Meta-Strategy Selector | Selects overarching strategies, determines the high-level approach that guide lower-level collaborative decision-making. |
| Negotiation Engine | Facilitates conflict resolution and resource allocation among agents, managing proposals and counter-proposals to reach mutually acceptable agreements |
| Interoperability & Bridging | Facilitates cross-platform and cross-ontology translation of protocols between diverse agent systems for seamless collaboration. |
| Decision Protocol Selector | Selects suitable decision-making models like voting, consensus, or leader-election. |
| Governance Protocol Selector | Selects the framework of rules and authority structures that dictate how agents operate, make decisions, and are managed within the system |
| Conflict Resolution Protocol | Implements a specific strategy, such as mediation or negotiation, to manage disagreements between agents and guide them toward a mutually agreeable solution |
| Reward Protocol Selector | Determines how to distribute incentives, either individually or to the team, to motivate agents and align their actions toward achieving the collective objective. |
Cognitive Libraries
| Library | Description |
|---|---|
| Skill Library | Contains reusable atomic capabilities that agents can acquire, activate, and compose into higher-level strategies to perform tasks. |
| Curriculum Library | Provides structured epistemic and operational scaffolds, like procedural references that can guide agents in how to think, learn, act, and adapt across domains and contexts. |
| Behavior Library | A collection of predefined or learned action patterns that agents can draw upon to respond to various situations, enabling reuse, mutation, or adapt, context-aware behaviors. |
| Planning Library | A store of algorithms, structured and reusable plans, subgoal templates that agents can utilize to formulate strategies and action sequences to achieve their goals. |
| Reasoning Library | A collection of logical frameworks and inference tools that empower agents to interpret information, draw conclusions, and make informed decisions. |
| Negotiation Library | A suite of protocols and strategies that enable agents to engage in dialogue, argumentation, bargaining, compromise, resolve conflicts, and come to agreements, particularly for resource allocation or coordinated actions. |
| Exploration Library | A set of algorithms that guide agents in exploring their environment to gather new information and discover potential paths, options, capabilities, rewards, which is essential for learning, adapting and openendedness. |
| Exploitation Library | A collection of strategies that allow agents to use their existing knowledge and learned behaviors to maximize their rewards, often balanced with exploration. |
| Decision Maker Library | A toolkit of models and algorithms that assist individual or groups of agents in selecting the best course of action through decision models, utility functions, and trade-off evaluators when faced with uncertainty. |
| Action Library | A catalog of executable primitives and complex actions that agents draw from when enacting plans or responding in real time. |
| Coalition Library | A set of protocols, reusable templates for forming, managing, and dissolving temporary or long term alliances, coordination tactics and group roles among agents to achieve shared goals. |
Compute Environments
| Component | Description |
|---|---|
| Sandboxes | An isolated, secure environment where agents can execute code or test behaviors without affecting the broader system. |
| Code Execution | The capability that allows an agent to run scripts or compiled code to perform computations or actions within its environment. |
| Code Generation | An agent's ability to write new code, enabling it to create novel solutions or adapt its functionalities to new tasks. |
| Simulator | A virtual environment that models or mimics a system, used for designing, evaluations, training, testing, and validating agent behaviors before deployment. |
| Policy Execution | Core system component responsible for governing agent behavior according to defined rules, permissions, constraints, and decision logic. It acts as a gatekeeper or arbiter. |
| Function Execution | An agent's ability to call predefined functions or API endpoints, allowing it to perform specific, encapsulated tasks. |
| Tool Execution | The capacity of an agent to utilize external software or hardware tools to extend its capabilities and accomplish its goals. |
Evaluator System
| Evaluator | Description |
|---|---|
| State Evaluator | A component that assesses the quality or value of the current situation (state) to help an agent decide on the best next action. |
| Alignment Evaluator | Measures how closely an agent's actions and outcomes adhere to human values, predefined policies, objectives, or ethical guidelines. |
| Policy Evaluator | Assesses whether a proposed action, plan, or behavior complies with defined policies before that action is executed. It performs runtime or planning-time checks to ensure that agent behavior remains within acceptable, safe, aligned, or permissible bounds. |
| Constraint Evaluator | Verifies whether an agent's proposed actions or plans comply with a set of predefined strict rules, limitations, or operational boundaries. |
| Result Evaluator | Analyzes the final outcome of a task to determine its SLA such as quality, accuracy, and overall success in achieving the intended goal. |
| Plan Evaluator | Examines an agent's sequence of intended actions (plan) to assess its coherence, feasibility, and efficiency before it is executed. |
| Progress Evaluator | Tracks and measures an agent’s ongoing performance over time to determine if it is making headway toward its ultimate objective. |
| Custom Evaluator | A flexible module that allows developers to define and apply their own unique metrics for assessing specific aspects of agent performance. |
| Prompt Evaluator | Analyzes and scores the effectiveness of the textual inputs (prompts) given to LLM-based agents to optimize their responses and behavior. |
Self Evolution & Self Improvement
| Component | Description |
|---|---|
| Prompt Optimization | Refines the textual inputs given to agents to maximize response quality and task performance through iterative improvement. |
| Workflow Optimization | Optimizes the sequence of actions and processes that agents follow to complete tasks based on various factors such as compute, accuracy, cost, tradeoffs. |
| Tool Optimization | Enhances the selection, configuration, and usage of external tools and resources to better accomplish agent objectives. |
| Curriculum Optimization | Strategically designing, ordering, and refining the learning or operational progression that an agent follows to maximize its efficiency, capability development, generalization, or alignment. |
| Iterative Feedback | Incorporates continuous performance analysis to identify areas for improvement and guide self-modification processes. |
| Self & External Reflection | Enables agents to analyze their own performance and incorporate external assessments to understand strengths and weaknesses, scope for learning, outcomes of their behaviors. |
| Active Exploration | Drives agents to proactively seek new experiences and knowledge to expand their capabilities beyond current limitations. |
| Mind Optimization | Enhances the agent's internal reasoning processes, memory management, and cognitive architecture for better behaviors. |
Reinforcement System
| Component | Description |
|---|---|
| Agent/Agency Policies | Defines the rules and strategies that govern how individual agents or groups of agents make decisions and take actions. |
| Observation System | Captures and processes state information from the environment to inform agent decisions and policy updates. |
| Reward Model | Defines how rewards are assigned to agent actions, based on outcomes, goals, or human-aligned values. |
| Reward Memory | Stores historical reward information to help agents learn from past experiences and improve future performance. |
| Credit Assignment System | Determines which actions or decisions were responsible for specific outcomes, enabling accurate learning. |
| Reward Learning | Adapts and refines the reward mechanisms based on experience to better align agent behavior with desired objectives. |