Jan-Peter v. Hunnius
09a0777f96
Evaluator overhaul: - Add Supersonic LUT trie evaluator (32M-entry, O(n) hand evaluation) - Add Cactus Kev perfect-hash 5-card evaluator (prime-product hashing) - 3-tier evaluation priority: Supersonic → Cactus Kev → Algorithmic - DashMap-cached 7-card evaluation for lock-free concurrent access - Rewrite JumpTable around CactusKevEvaluator + DashMap cache Bot framework: - Add StrategyBot adapter (Strategy trait → HoldemPlayer) - Add register_bot_type() for plugin-style bot registration - Add strategy module with modular composable strategies Repository split: - Remove holdem_bots from workspace (moved to private super_marvin repo) - Remove holdem_bots dependency from holdem_sim - Update cash_game.toml to use built-in bots only - Clean up .gitignore (remove stale holdem_bots exclusion) - Delete plans/ directory (internal planning artifacts) Documentation: - Add ARCHITECTURE_SUPERSONIC_EVALUATOR.md - Add REFERENCES.md - Update ROADMAP.md and VISION.md - Remove outdated docs (ACHIEVEMENTS, RAKE, TOURNAMENT_RAKE, meerkat-alignment)
2.2 KiB
2.2 KiB
Poker AI Testbed & Live Server Vision
Overall Goal
Create a comprehensive poker AI ecosystem with two main components:
- Massive Simulation Testbed – For developing and testing bot strategies across all game types (NL/FL/PL, Cash/SNG/MTT) with configurable parameters
- Live Action Server – For deploying bots in real poker environments with automatic table selection
Core Architecture Components
1. Simulation Testbed
- Configurable bots (Rule-based, Nash EQ, Statistical, Hand-reading, Reinforcement Learning)
- Mass parallel simulations with GPU acceleration (e.g., for turn and river rollouts)
- Multi-tier hand evaluation: Supersonic LUT trie → Cactus Kev perfect-hash → Algorithmic fallback, with DashMap-cached 7-card evaluation
- TOML-driven configuration for all parameters of bots and simulations
- Comprehensive result analysis and bot evolution
2. Live Action Server
- Generic protocol for client communication
- Early folding capability (bots can fold without being polled)
- Multiple client adapters for different poker sites
- Automated table selection based on game configuration
- Real-time strategy adaptation
3. Bot Concepts
- Modular Strategy per stage and game situation – e.g., low stack in a tournament, preflop vs. postflop.
Plugable sub-strategies and decision methods (first applicable, random, most aggressive, least aggressive, etc.) - Generic helper functions for strategies like ICM, ppot, not, hand strength, against one and multiple opponents
- Incremental, asynchronous rollout of turn and river on flop and river on turn
- Flop Playability score for preflop based on precalculated rollouts for all possible flops and starting hands
- Opponent hand prediction and statistics, for instance in Poker Tracker format
- Real-time strategy adaptation, e.g., reinforcement learning
Expected Outcomes
- Research Platform: Systematic testing of poker AI strategies
- Live Deployment: Bots that can play on real poker sites
- Strategy Insights: Understanding what works in different game conditions
- Bot Evolution: Self-improving systems through simulation and adaptation