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Dragan Spiridonov
eebb76731e
Milestone 3 — Scale & Optimization (R7-R10): - R7: Meta-learning enhancements (DecayingBeta, PlateauDetector with CUSUM, ParetoFront, CuriosityBonus) wired into DomainTransferEngine - R8: PageRank pattern importance solver with citation graph pipeline (PatternCitationGraph bootstraps from 129 existing patterns, blended scoring in pattern-promotion.ts) - R9: Spectral graph sparsifier (degree-based leverage heuristic) wired into mincut-wrapper.ts as optional preprocessing - R10: Reservoir replay buffer with coherence-gated admission and CUSUM drift detection, wired into ExperienceReplay (write + read paths) Milestone 4 — Advanced Learning (R11-R12): - R11: E-prop online learning (12 bytes/synapse, eligibility traces, feedback alignment) — RL algorithm #10, extends BaseRLAlgorithm - R12: Granger causality for test failure prediction (VAR + F-test with full statistical math) wired into defect-intelligence coordinator with persistent history accumulation Infrastructure: - 8 feature flags (all default true per opt-out policy), convenience functions, env var support, CLI descriptions - RLAlgorithmType union: 9 → 10 members (added 'eprop') - ADR-087 status: Proposed → Active (M1-4 complete) - 234 new tests across 8 test files, all passing - Performance benchmarks for PageRank, sparsification, reservoir admission - 0 regressions in existing test suite Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>