Poker AI Testbed & Live Server Vision

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

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

Perfect Hash Jump Tables: Revolutionary memory-efficient evaluation (~130MB vs 625MB)
Suit Canonicalization: Advanced isomorphic hand reduction for optimal performance
Bottom-up Trie Construction: Cache-optimized memory layout for CPU efficiency
Zero Breaking Changes: Full backward compatibility with existing evaluation APIs

Configurable bots (Rule-based, Nash EQ, Statistical, Hand-reading, Reinforcement Learning)
Mass parallel simulations with GPU acceleration (e.g., for turn and river rollouts)
Memory-efficient evaluation: 79% memory reduction enables larger-scale simulations
TOML-driven configuration for all parameters of bots and simulations
Comprehensive result analysis and bot evolution

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