neural-training

Neural Training Skill Purpose Train and optimize neural patterns using SONA, MoE, and EWC++ systems. When to Trigger Training new patterns Optimizing agent routing Knowledge consolidation Pattern recognition tasks Intelligence Pipeline RETRIEVE — Fetch relevant patterns via HNSW (150x-12,500x faster) JUDGE — Evaluate with verdicts (success$failure) DISTILL — Extract key learnings via LoRA CONSOLIDATE — Prevent catastrophic forgetting via EWC++ Components Component Purpose Performance SONA Self-optimizing adaptation <0.05ms MoE Expert routing 8 experts HNSW Pattern search 150x-12,500x EWC++ Prevent forgetting Continuous Flash Attention Speed 2.49x-7.47x Commands Train Patterns npx claude-flow neural train --model-type moe --epochs 10 Check Status npx claude-flow neural status View Patterns npx claude-flow neural patterns --type all Predict npx claude-flow neural predict --input "task description" Optimize npx claude-flow neural optimize --target latency Best Practices Use pretrain hook for batch learning Store successful patterns after completion Consolidate regularly to prevent forgetting Route based on task complexity