Jan-Peter v. Hunnius
17d0440c86
- Refactor AlgorithmicEvaluator from stateful Arc<Evaluator> wrapper to pure stateless evaluator with zero-allocation construction - Extract shared evaluation logic into pub(crate) methods, eliminating ~220 lines of duplicated code from Evaluator - Add game module: table, hand runner, tournament, bots, config, stats - Add holdem_sim CLI binary crate for running simulations - Convert MathEvaluator to thread-safe singleton with Arc<Inner> pattern - Replace heap-allocated combination generation with const-generics stack-based approach in AlgorithmicEvaluator::evaluate_n_card_hand - Add thiserror 2 dependency for GameError derive - Update docs: README, ACHIEVEMENTS, ROADMAP
103 lines
No EOL
3.1 KiB
Markdown
103 lines
No EOL
3.1 KiB
Markdown
# Poker AI Testbed & Live Server Roadmap
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## Step-by-Step Implementation Plan
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### Phase 1: Foundation
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**Basic poker engine**
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- Game state management
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- Game Info and Player Info traits
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- Event reporting and action scheme
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- Basic game rules (NL/FL/PL)
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**Configuration system**
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- TOML configuration structures
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- Bot parameter configuration
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- Game type configurations (Cash/SNG/MTT, buyins, blinds, hands per level, etc.)
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- Simulation parameters (hands/tournaments count, buyin thresholds for bots, etc.)
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### Phase 2: Simulation Testbed ✅
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**Goal:** Mass simulation capability
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**Testbed core** ✅
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- Tournament/cash game runners ✅
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- Result collection and analysis ✅
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- Bot interface with early folding capability ✅
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- Bot performance metrics & summary ✅
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- Simulation and game factories ✅
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- Configuration-driven experiment runner ✅
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- Seed control for reproducibility ✅
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**Remaining for mass simulation**
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- Parallel simulation engine (multi-threading)
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- Result visualization (charts/graphs)
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- Rebuy/addon support for tournaments
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---
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### Phase 3: Bot Framework
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**Goal:** All bot types with playability enhancement
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**Bot core implementations** (partially complete — basic bots exist)
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- ~~Generic helper functions for strategies~~ (basic bots done: CallBot, FoldBot, RaiseBot, RandomBot)
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- Modular Strategy per stage and game situation
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- Rule-based bot with configurable thresholds – port from Java
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- Nash equilibrium calculator for SNG endgame – port from Java
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- Statistical tracking bot – port from Java
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- Logging of decision-making process
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**Advanced bots**
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- GPU acceleration for mass rollouts
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- Hand-reading opponent modeling (possibly with GPU integration)
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- Flop playability precomputation & score integration
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- Basic reinforcement learning skeleton
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- Hybrid bot combining multiple approaches
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- Factory for bot and sub-strategy composition
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- Genetic algorithm for bot evolution (via configuration files)
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---
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### Phase 4: "Unit Test" Framework
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**Goal:** Bot behavior can be tested against predefined hands
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**Hand Replayer**
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- Poker Tracker style hands
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- Action comparison to expected outcome
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- Selection of hands from different sources (books)
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- Action likelihoods (multiple replays)
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---
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### Phase 5: Live Server Infrastructure
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**Goal:** Real-time bot deployment
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**Server core**
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- Network protocol design (TBD: WebSocket, JSON, MQ, etc.)
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- Actions (incl. early fold and table selection), events (incl. table switches and available tables)
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- Client registration and management
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- Game state synchronization
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- Action dispatch system
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- Event logging for analysis of problems
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**Client adapter system**
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- Client factory for different poker environments
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- Screen / protocol scraping adapters
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- Table selection logic
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- Configuration-driven game selection
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---
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### Phase 6: Integration & Polish
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**Goal:** Production-ready system
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**Advanced features**
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- Real-time strategy adaptation
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- Multi-table coordination
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- Bankroll management
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- Risk adjustment based on results
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**Optimization and deployment**
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- Performance profiling and optimization
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- Error handling and recovery
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- Documentation and examples
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- Deployment scripts and configuration |