Individual skill
self-optimization
SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.
library/methodologies/ruflo/skills/self-optimization/SKILL.md
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- Improving routing and agent selection over time
- Adapting to new project patterns without forgetting old ones
- Building cross-session intelligence
## SONA Cycle
1. **Extract Patterns** - Mine execution data for recurring patterns
2. **RETRIEVE** - Search ReasoningBank for matching trajectories
3. **JUDGE** - Evaluate trajectory applicability in current context
4. **DISTILL** - Compress and store new entries
5. **Adapt** - Update weights with EWC++ regularization
## Anti-Forgetting (EWC++)
