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Ouroboros – Distributed Self-Improvement

Status: TRL-4 (laboratory-validated)

Ouroboros is the recursive self-improvement loop of the BlackSwan swarm. It combines a genetic engine, champion/challenger deployment, and distributed genome exchange to continuously optimise trading strategies.

Key components

  • GeneticEngine (sim/genetic_engine.py) – population-based evolution with crossover, mutation, and elitism.
  • Champion/Challenger – new strategies are shadow-tested before replacing the active champion.
  • Genome exchange – nodes share their best genomes via Redis pub/sub (legacy) or CRDT‑Gossip (decentralised).

Formal verification

The invariant V_s > V_h (improvement rate exceeds degradation rate) is proved in formal/tla/Ouroboros.tla and monitored live in the swarm logs.

Observed performance

  • Kelly parameters converge to max_risk_per_trade ≈ 0.20, phi_llm ≈ 0.15.
  • Capital growth ratio exceeds 7× compared to static strategies.