Phase 4: Distributed Cognitive Mesh API & Embodiment Layer

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Phase 4: Distributed Cognitive Mesh API & Embodiment Layer\n\n## Objective\nExpose the network via REST/WebSocket APIs; bind to Unity3D, ROS, and web agents for embodied cognition.\n\n## Implementation Steps\n- [ ] Architect distributed state propagation APIs\n- [ ] Design task orchestration REST endpoints\n- [ ] Implement WebSocket real-time communication\n- [ ] Create GraphQL interface for complex queries\n- [ ] Implement Unity3D cognitive integration interface\n- [ ] Create ROS (Robot Operating System) bindings\n- [ ] Design WebSocket interfaces for web agents\n- [ ] Implement bi-directional data flow protocols\n- [ ] Verify real-time embodiment capabilities\n\n## API Specifications\n### REST Endpoints\n- GET /api/v1/cognitive/state - Get current cognitive state\n- POST /api/v1/cognitive/process - Submit cognitive task\n- GET /api/v1/attention/allocation - Get attention distribution\n- POST /api/v1/agents/register - Register new agent\n\n### WebSocket Events\n- cognitive.state.update - Real-time state changes\n- attention.allocation.change - Attention shifts\n- agent.registration - New agent connections\n- task.completion - Task processing results\n\n## Success Criteria\n- ✅ REST API provides complete cognitive network access\n- ✅ WebSocket connections handle real-time bidirectional communication\n- ✅ Unity3D integration enables 3D cognitive embodiment\n- ✅ ROS bindings support robotic cognitive applications\n- ✅ System handles 1000+ concurrent agent connections\n\nPart of the Distributed Agentic Cognitive Grammar Network development cycle.