- Implement comprehensive tests for adaptive learning mechanisms including MicroLoRA and SONA in learning_tests.rs.
- Introduce tests for bio-inspired neural components such as HDC, BTSP, and Spiking Neural Networks in nervous_system_tests.rs.
- Create common utilities for random vector generation, vector assertions, and softmax calculations in mod.rs.
- Ensure all tests validate expected behaviors and maintain numerical stability.
Four attention mechanisms answering fundamental questions:
- Neural Attention: What words/tokens matter?
- DAG Attention: What computational steps matter?
- Graph Attention: What relationships matter?
- State Space: What history still matters?
Includes:
- dag_attention.rs: Critical path analysis, topological ordering
- attention_unified.rs: Unified interface composing all 4 types
- Updated mod.rs architecture diagram
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Enable capabilities module with pub export
- Add compute/ module with SIMD, WebGPU, WebGL backends
- Add ai/ module with attention, router, federated learning, LoRA
- Streamline WASM API for Time Crystal, NAO, MicroLoRA, HDC, WTA, BTSP
- Add Global Workspace and Morphogenetic network support
- Add learning scenarios for error recovery and file sequences
- Add swarm collective intelligence and consensus modules
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Critical security fixes before production deployment:
1. Argon2id PBKDF in pikey/mod.rs (replaces SHA-256)
- Memory-hard KDF with 64MB memory, 3 iterations
- Version 0x02 format with salt, backward compatible with v1
- Secure zeroization of key material
2. Ed25519 signature verification in rac/mod.rs
- Real cryptographic verification for authority resolutions
- ScopedAuthority::sign_resolution() helper for signing
- Canonical message format for verification
3. Password-protected key export in identity/mod.rs
- export_secret_key now requires 8+ character password
- AES-256-GCM encryption with Argon2id-derived key
- import_secret_key for secure recovery
Dependencies added:
- argon2 v0.5 (memory-hard KDF)
- zeroize v1.7 (secure memory cleanup)
Test coverage:
- 125 tests passing (40 lib + 85 integration)
- Updated adversarial tests with real Ed25519 signatures
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
## Learning Module (src/learning/mod.rs)
- ReasoningBank for pattern storage with similarity lookup and pruning
- TrajectoryTracker ring buffer for task execution tracking
- Spike-driven attention for 87x energy efficiency (based on Yao et al.)
- Multi-head attention for distributed task routing
- NetworkLearning unified interface for edge nodes
## RAC Module (src/rac/mod.rs) - Adversarial Coherence Thesis
Implements the 12 axioms for browser-scale adversarial truth maintenance:
1. Connectivity is not truth
2. Everything is an event
3. No destructive edits (deprecation only)
4. Every claim is scoped
5. Semantics drift is expected
6. Disagreement is signal
7. Authority is scoped, not global
8. Witnesses matter
9. Quarantine is mandatory
10. All decisions are replayable
11. Equivocation is detectable
12. Local learning is allowed
Core components:
- Append-only Merkle event log for tamper-evident history
- CoherenceEngine for conflict detection and resolution
- QuarantineManager for contested claims
- Authority policy and verifier traits
- Decision traces for audit and replay
## Integration
- Learning and RAC integrated into EdgeNetNode
- 28 tests pass (13 new tests for learning/RAC)
References:
- FLP Impossibility (MIT CSAIL)
- PBFT Byzantine Fault Tolerance
- CRDTs (Lip6)
- RFC 6962 Certificate Transparency
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
