Evolving Poker is a live agent-evaluation playground where three AI models compete in a simplified poker game and adapt their strategies after every hand. Each player starts with the same strategy—aggression, bluff rate, and call threshold—while a deterministic game engine handles cards, betting, and legal actions. After each hand, the agents review the outcome and decide whether to change their strategy or keep it unchanged. Every update is shown as a readable diff, allowing viewers to compare which model learns effectively, which overreacts to noisy results, and which offers the best balance of performance, latency, and cost. Pioneer runs and compares the models, Band coordinates the agents and records their reflections, and Replay tests the spectator dashboard. The final tournament results and evolution history are published to cited.md, with the full audit report available through an x402-protected endpoint.
