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Self-Reflective Training (Step 6): - Knowledge imbalance detection (>40% in one category) - Dynamic SONA threshold adaptation (lower on 0 patterns, raise on success) - Vote coverage monitoring with auto-correction Curiosity Feedback Loop (Step 7): - Stagnation detection via delta_stream - Auto-generates synthesis memories for under-represented categories - Creates self-sustaining knowledge velocity Auto-Reflection Memory (Step 8): - Brain writes searchable self-reflections after each training cycle - Persistent learning history enables meta-cognitive search Symbolic Inference Engine: - Forward-chaining Horn clause resolution with chain linking - Transitive inference across propositions - Self-loop prevention, confidence filtering - 3 new tests passing SONA Threshold Optimization: - min_trajectories: 100→10 (primary blocker) - k_clusters: 50→5, min_cluster_size: 2→1 - quality_threshold: 0.3→0.15 - Added runtime set_quality_threshold() API Co-Authored-By: claude-flow <ruv@ruv.net> |
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| .. | ||
| export | ||
| loops | ||
| training | ||
| engine.rs | ||
| ewc.rs | ||
| lib.rs | ||
| lora.rs | ||
| mod.rs | ||
| napi.rs | ||
| napi_simple.rs | ||
| reasoning_bank.rs | ||
| time_compat.rs | ||
| trajectory.rs | ||
| types.rs | ||
| wasm.rs | ||