rUv b69f51bbd7 feat: Full v2.1 upgrade with multi-algorithm learning and TensorCompress (v0.1.69) ... ## Multi-Algorithm Learning Engine - 9 algorithms: q-learning, sarsa, double-q, actor-critic, ppo, decision-transformer, monte-carlo, td-lambda, dqn - Task-specific configuration: - agent-routing: double-q (reduces bias) - error-avoidance: sarsa (conservative) - confidence-scoring: actor-critic (continuous) - trajectory-learning: decision-transformer (sequence) - context-ranking: ppo (stable) - memory-recall: td-lambda (traces) ## TensorCompress (10x Memory Savings) - 5 compression levels based on access frequency: - none (hot >0.8): 0% savings - half (warm >0.4): 50% savings - pq8 (cool >0.1): 87.5% savings - pq4 (cold >0.01): 93.75% savings - binary (archive ≤0.01): 96.9% savings - Auto-compression on session-end ## Pretrain Phases (11 total) - Phase 10: Multi-algorithm learning bootstrap - Phase 11: TensorCompress initialization ## Environment Variables (v2.1) - RUVECTOR_MULTI_ALGORITHM=true - RUVECTOR_DEFAULT_ALGORITHM=double-q - RUVECTOR_TENSOR_COMPRESS=true - RUVECTOR_AUTO_COMPRESS=true 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>		2025-12-31 15:24:30 +00:00
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intelligence.json	feat: Full v2.1 upgrade with multi-algorithm learning and TensorCompress (v0.1.69)	2025-12-31 15:24:30 +00:00