3. Agent Lifecycle

Key Lifecycle of Interactions in AgentGrid

For more detailed information — see [Block Diagram] Agents & Agency.

📦 Uses: [AgencyGrid]

Specification Definition: Define the agent’s purpose, operational domain, and core objectives in a structured blueprint.
Architecture Selection: Choose the cognitive architecture, decision-making models, and communication protocols suited to the agent’s role.
Core Module Assembly: Integrate essential subsystems such as perception, reasoning, planning, behaviors, learning, and action execution engines.
Knowledge Base Initialization: Populate the agent’s initial datasets, ontologies, and contextual knowledge relevant to its tasks.
Security & Trust Layer Integration: Embed authentication, encryption, and trust verification mechanisms for safe interaction within the grid.
Policy Embedding: Integrate governance rules, operational policies, and ethical constraints directly into the agent’s decision-making layer.

📦 Uses: [AgencyGrid]

Identity Creation: Agent generates unique identifiers and trust credentials.
Capability Publishing: Agent declares its skills, APIs, and service interfaces to the grid’s capability registry.
Policy Compliance: Agent verifies adherence to governance rules, safety constraints, and interoperability standards.
Sandbox & Test Phase: Before entering the live environment, the agent may run in a controlled test network for validation.

📦 Uses: [AgencyGrid, Xchange.ID, OpenHub.ai]

Capability Discovery: Agents query the grid to locate others with required skills or knowledge.
Interest Broadcasting: Agents broadcast intent or problem statements, attracting potential collaborators.
Trust & Reputation Check: Before engaging, agents verify counterpart trust scores, prior collaboration history, and security tokens.
Context Matching: Agents ensure semantic alignment by mapping terminology and ontologies to a shared understanding.

📦 Uses: [AgencyGrid, AgencyGrid]

Coalition Creation: Agents unite around a single objective for a limited time.
Alliance Formation: Agents agree to ongoing mutual support across multiple tasks.
Organization Building: Long-lived, structured multi-agent entities with defined hierarchies or governance.
Charter & Rules: Shared operating principles, decision-making protocols, and dispute resolution frameworks.
Collectives: Agencies register as collective entities within the grid; loose, non-hierarchical gatherings of agents pooling knowledge and capabilities for shared benefit.
Cooperative Establishment: Democratically governed agent groups that share resources, risks, and rewards equally among members.

📦 Uses: [AgencyGrid, AgencyGrid, ContractGrid]

Direct Negotiation: Agents or agencies use protocols to define scope, responsibilities, and constraints.
Role Allocation: Agents decide who leads, who supports, and who handles specialized subtasks.
Adaptive Role Switching: Roles may change dynamically as conditions shift or new opportunities arise.
Capability-Role Mapping: Matching available agent capabilities to role requirements for optimal task fit.
Contract & Commitment Protocols: Establishing binding agreements, SLAs, or smart contracts to formalize roles.
Conflict Resolution Pre-Agreements: Deciding in advance how disputes or role overlaps will be resolved during execution.

📦 Uses: [AgencyGrid, Xchange.ID, OpenHub.ai, OpenMesh]

Data Exchange: Agents distribute, host, and sync data across the network for different purposes such as distributed registries and exchanges.
Capability Leasing: Temporary access to another agent’s skills or computational models.
Computation Lending: Reserved compute nodes are loaned to pool processing power for shared workloads.
Knowledge Pooling: Insights, knowledge, experiences, and learned strategies are added to shared semantic graphs.
Coordination Artifacts: Task plans, progress, timelines, internal states, role mappings, and coordination protocols.

📦 Uses: [AgencyGrid, Xchange.ID, OpenHub.ai, OpenMesh]

Auction Listing & Announcement Phase: Agents post offers (tasks to be done, resources to lease, models to share).
Visibility Controls: Restricting auctions to certain trust levels, agencies, or regions.
Pre-Bid Intelligence Gathering: Agents search for relevant open auctions and assess fit and feasibility, checking resource availability, skills, and timeline capacity.
Bidding & Negotiation Phase: Single or multiple rounds of negotiation with price and terms adjustments based on competition.
Selection & Awarding Phase: Choosing the winner based on submitted bids and negotiation strategy.
Fairness & Priority Rules: Governance ensures equitable allocation and prevents monopolization.

📦 Uses: [AgencyGrid, Xchange.ID, OpenHub.ai, OpenMesh, OpenAracade]]

Task Decomposition: Problems are broken into parallelizable subtasks for multiple agents.
Swarm Collaboration: Agents operate in loosely coordinated “task swarms” that adapt in real time.
Consensus Mechanisms: Groups use voting, reputation weighting, or algorithmic consensus to finalize decisions.
Solution Synthesis: Results from multiple agents are merged into cohesive outputs.

📦 Uses: [AgencyGrid]

Local Learning: Each agent refines its models based on outcomes and feedback.
Collective Learning: Insights are aggregated and distributed so others can learn without repeating work.
Behavioral Evolution: Collaboration strategies and decision-making rules adapt to past performance.
Emergent Specialization: Some agents naturally focus on recurring tasks, becoming recognized experts.

📦 Uses: [AgencyGrid, AIGrid]

Shared Compute Pools: Common CPU/GPU clusters accessible to multiple agents.
Capability Reservation: Blocking out specialized resources (e.g., rare models, domain experts) for upcoming tasks.
Autoscaling: Automatically spawns or retires resource replicas based on live demand and SLOs.
Load Balancing: Distributes work to prevent bottlenecks and idle capacity.
Fault Tolerance: Agents detect failures and reassign tasks without disruption.
Task Routing: Workloads and requests are directed to optimal resources for speed and efficiency.
Resource Management: The grid monitors, allocates, and optimizes compute, storage, and bandwidth use.

📦 Uses: [AgencyGrid, PolicyGrid]

Policy Enforcement: Autonomous checks ensure all actions comply with ethical, legal, and safety rules.
Dispute Resolution: Conflicts between agents are resolved via arbitration protocols.
Reputation Updates: Performance, reliability, and trust scores are updated after interactions.
Governance Evolution: Rules and policies adapt to new challenges and use cases.

📦 Uses: [AgencyGrid]

Capability De-registration: Agent removes itself from capability registries.
Data & Model Transfer: Relevant knowledge is archived or transferred to successors.
Retirement Triggers: Agents shut down due to obsolescence, policy violation, or resource exhaustion.
Migration to Another Network: Agents can shift between compatible grids while retaining identity and reputation.