docs(research): Add autonomous agent runtime architecture research

Created 17,000-word research document exploring eBPF/sBPF as a universal
autonomous agent runtime, bridging AI agent theory with blockchain execution.

**10 Major Research Areas:**

1. **Autonomous Agent Theory**
   - Perception-Reasoning-Action (PRA) loop
   - Reactive, Deliberative, Hybrid architectures
   - Bounded rationality in resource-constrained environments
   - BDI (Belief-Desire-Intention) framework

2. **eBPF as Agent Runtime**
   - 7 properties making eBPF ideal for agents
   - Verifiable safety, deterministic execution
   - Resource metering, event-driven architecture
   - Agent lifecycle: birth → active → dormant → death
   - Complete resource management framework

3. **Multi-Agent Systems on Blockchain**
   - Deterministic multi-agent execution via consensus
   - Agent coordination patterns (leader-follower, cooperative, competitive)
   - Game theory: Nash equilibrium, MEV auctions
   - Consensus makes MAS deterministic and trustless

4. **Agent Communication Patterns**
   - Shared memory (accounts)
   - Ring buffers (lock-free FIFO)
   - Message passing (CPIs)
   - Publish-subscribe (topic-based events)

5. **Agent Architectures**
   - Blackboard architecture (shared knowledge)
   - Subsumption architecture (layered behaviors)
   - Cognitive architecture (ACT-R production rules)
   - Complete OVSM implementations for each

6. **Economic Agent Systems**
   - Agents with skin-in-the-game
   - Staking, slashing, reputation systems
   - Fee-based competition (MEV auctions)
   - Incentive calibration via real capital risk

7. **Agent Learning and Adaptation**
   - Online learning (incremental weight updates)
   - Q-learning (reinforcement learning on-chain)
   - Meta-learning (learning to learn)
   - Lightweight adaptation within CU constraints

8. **Security and Verification**
   - Verifier-enforced safety guarantees
   - Capability-based sandboxing
   - Formal verification of agent behavior
   - Safe agent templates

9. **Production Multi-Agent Systems**
   - 10-agent trading system architecture
   - Data agents + strategy agents + risk + execution
   - Swarm intelligence (particle swarm optimization)
   - Agent coordination via blackboard

10. **Future Research Directions**
    - Neuro-symbolic agents (NN + logic)
    - Multi-chain coordination
    - Quantum-resistant cryptography
    - Constitutional AI (ethical constraints)

**Key Theoretical Contributions:**

- **PRA Loop Mapping**: Shows how agent perception-reasoning-action
  maps perfectly to eBPF's hook→execute→commit model

- **Deterministic MAS**: Proves blockchain consensus enables
  deterministic multi-agent systems (impossible in distributed systems)

- **Bounded Rationality by Design**: Compute unit limits force agents
  to use satisficing heuristics (Herbert Simon, Nobel 1978)

- **Economic Agents**: Shows how skin-in-the-game changes agent
  behavior fundamentally (calibrated confidence, risk management)

- **Verifiable Autonomy**: eBPF verifier enables untrusted autonomous
  code to run in critical infrastructure (kernel/validators)

**Complete Code Examples:**

- 300+ lines: BDI agent with belief-desire-intention reasoning
- 200+ lines: Hybrid 3-layer agent (reactive + tactical + deliberative)
- 150+ lines: Production rule system (cognitive architecture)
- 100+ lines: Q-learning agent with online adaptation
- 250+ lines: Multi-agent blackboard coordination system

**Impact:**

This research establishes eBPF/sBPF as the ideal foundation for
autonomous economic agents in trustless multi-agent economies. The
combination of safety, determinism, resource metering, and economic
incentives creates a fundamentally new computing paradigm: **code that
makes decisions, takes risks, and adapts autonomously with verifiable
execution and cryptographic commitment enforcement.**

Completes the eBPF research series with agent-theoretic foundations.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

Author: 0xrinegade