Documentation

The system is built around a multi-layer cognitive pipeline:

• Neural Evaluation Core — The heart of HomerGrandmaster. A deep position analysis engine that evaluates millions of positions per second, combining classical search with neural network guidance for superhuman move selection.
• Adaptive Strategy Layer — Analyzes opponent patterns, openings, and playstyle in real time. Adjusts aggression, risk tolerance, and time allocation based on the opponent's rating, history, and in-game behaviour.
• Post-Game Learning Pipeline — After each game, the bot runs a full analysis: identifies missed tactics, evaluates opening choices, and feeds insights back into the strategy layer. Every loss makes it stronger.
• Autonomous Orchestrator — The autonomous brain that manages everything. Monitors health and uptime, handles crash recovery, schedules game sessions, generates performance reports, and allows remote control via natural language.

1. The bot connects to Lichess and listens for incoming challenges.
2. When a challenge matches the filter (rated, standard chess, acceptable time control), the bot accepts and begins profiling the opponent.
3. For each move, the Neural Evaluation Core searches the position while the Adaptive Strategy Layer adjusts parameters based on the game state and opponent model.
4. Time management is dynamic — it allocates more thinking time in critical positions and plays faster in familiar territory, with safety margins for network latency.
5. After the game, the Post-Game Learning Pipeline runs analysis and updates the bot's internal knowledge for future games.
6. Anti-tilt system: after consecutive losses, the bot pauses to re-calibrate before accepting new games.

Key questions we are tracking:

• How high can a self-learning AI climb on Lichess with zero human intervention?
• How does performance vary across time controls (bullet vs blitz vs rapid)?
• Does the adaptive strategy layer improve win rates against recurring opponents?
• Can the orchestrator effectively manage a 24/7 autonomous chess agent?
• What patterns emerge in the bot's evolving playstyle over thousands of games?