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AdaptiveIntelligenceCircle/AIC-agents

AIC-agents

IBCS and introspective behavior.

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README.md

Overview

AIC-agents is a core repository in the AIC ecosystem, focusing on autonomous, accountable, and cooperative agents designed to operate across edge devices, local systems, and decentralized environments.

Unlike conventional AI agents optimized for scale and data centralization, AIC-agents emphasizes:

  • Human-aligned autonomy
  • Local-first and edge-native execution
  • Explicit trust, rollback, and responsibility models
  • Long-term survivability without dependency on centralized infrastructure

This repository is designed to be:

  • Research-friendly (clear abstractions, inspectable behavior)
  • Production-aware (security, failure handling, lifecycle management)
  • Ethically grounded (human-in-the-loop, non-extractive design)

Core Philosophy

AIC-agents is not about maximizing capability at all costs. It is about:

  • Bounded intelligence
  • Contained autonomy
  • Auditable decision-making
  • Reversible actions

Every agent is treated as a participant in a system, not an opaque optimizer.


High-level Architecture

AIC-agents/
├── core/               # Agent lifecycle, identity, state
├── cognition/          # Reasoning, planning, introspection
├── trust/              # Trust evaluation, reputation, policy
├── execution/          # Action execution, sandboxing
├── rollback/           # Reversibility, damage control
├── communication/      # Agent-to-agent & agent-to-system protocols
├── simulation/         # Testing, adversarial & what-if scenarios
├── policies/           # Behavioral and ethical constraints
└── docs/               # Research notes & design rationale

Each folder is intentionally modular and can evolve independently.


Agent Lifecycle

  1. Initialization (Identity, Capability Declaration)
  2. Context Acquisition
  3. Reasoning & Constraint Evaluation
  4. Action Proposal
  5. Trust & Policy Validation
  6. Execution or Rejection
  7. Monitoring & Feedback
  8. Rollback / Adaptation (if required)

Relationship to Other AIC Repos

  • AIC-edgeOS: provides execution substrate
  • AIC-orchestration: coordinates multi-agent behavior
  • AIC-research: formal models & academic grounding
  • AIC-earth: societal and macro-level framing

AIC-agents can run standalone, but gains strength when composed.


Status

This repository is under active research and architectural development. APIs, folder structures, and abstractions may evolve.


Final Note

If you are looking to build uncontrolled, extractive, or opaque AI systems, this project is likely not for you.

If you are willing to build slowly, responsibly, and honestly — welcome.

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IBCS and introspective behavior.

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