TexasHoldemAgent is an open-source reinforcement learning AI agent designed to master heads-up limit Texas Hold’em poker. It uses deep Q-networks and simulated gameplay to adaptively learn betting strategies, evaluate hand strength, and make real-time decisions. Researchers and enthusiasts can train the agent from scratch, use pre-trained models, analyze opponent behavior, and benchmark different strategies, providing a comprehensive toolkit for AI-driven poker strategy research and development.
AI Platforms & Frameworks
Research
Gaming
#poker AI
#Texas Hold'em simulation
#reinforcement learning
#DQN poker
#hand evaluation
#game strategy
#AI training
#custom poker AI
#Performance Metrics
#AI gaming research
#real-time evaluation
#modular framework
#deep learning poker
#GPU Acceleration
#Pre-trained models
#policy improvement
#batch simulation
#Open-source AI
#poker strategy development
#decision-making algorithms
...
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TexasHoldemAgent
TexasHoldemAgent is an open-source reinforcement learning AI agent designed to master heads-up limit Texas Hold’em poker. It uses deep Q-networks and simulated gameplay to adaptively learn betting strategies, evaluate hand strength, and make real-time decisions. Researchers and enthusiasts can train the agent from scratch, use pre-trained models, analyze opponent behavior, and benchmark different strategies, providing a comprehensive toolkit for AI-driven poker strategy research and development.
AI Platforms & Frameworks
Research
Gaming
#poker AI
#Texas Hold'em simulation
#reinforcement learning
#DQN poker
#hand evaluation
#game strategy
#AI training
#custom poker AI
#Performance Metrics
#AI gaming research
#real-time evaluation
#modular framework
#deep learning poker
#GPU Acceleration
#Pre-trained models
#policy improvement
#batch simulation
#Open-source AI
#poker strategy development
#decision-making algorithms
...
Featured
What is TexasHoldemAgent?
TexasHoldemAgent provides a modular environment built on Python to train, evaluate, and deploy an AI-powered poker player for heads-up limit Texas Hold’em. It integrates a custom simulation engine with deep reinforcement learning algorithms, including DQN, for iterative policy improvement. Key capabilities include hand state encoding, action space definition (fold, call, raise), reward shaping, and real-time decision evaluation. Users can customize learning parameters, leverage CPU/GPU acceleration, monitor training progress, and load or save trained models. The framework supports batch simulation to test various strategies, generate performance metrics, and visualize win rates, empowering researchers, developers, and poker enthusiasts to experiment with AI-driven gameplay strategies.
Who will use TexasHoldemAgent?
- AI researchers
- Reinforcement learning students
- Poker enthusiasts
- Game AI developers
- Educators in AI
How to use the TexasHoldemAgent?
- Step1: Clone the repository from GitHub using git clone https://github.com/YiCheng996/TexasHoldemAgent.git
- Step2: Install required Python dependencies via pip install -r requirements.txt
- Step3: Configure training parameters in config.py (e.g., learning rate, episodes)
- Step4: Run training script python train.py to start reinforcement learning
- Step5: Evaluate performance using python evaluate.py with test scenarios
- Step6: Use python play.py to simulate games with pre-trained models
- Step7: Analyze results, visualize metrics, and fine-tune hyperparameters as needed
Platform
- mac
- windows
- linux
TexasHoldemAgent's Core Features & Benefits
The Core Features
- Reinforcement learning training pipeline
- Deep Q-network for decision making
- Custom Texas Hold’em simulation environment
- Hand strength evaluation
- Pre-trained model support
- CPU/GPU acceleration
- Performance visualization tools
The Benefits
- Accelerates AI-driven poker strategy research
- Modular and customizable codebase
- Open-source and extensible framework
- Pre-trained models for instant evaluation
- Comprehensive training and analysis tools
TexasHoldemAgent's Main Use Cases & Applications
- AI research on poker strategy
- Educational tool for reinforcement learning
- Benchmarking poker bots
- Simulating betting strategies
- Developing custom decision-making agents
FAQs of TexasHoldemAgent
TexasHoldemAgent Company Information
- YiCheng996
TexasHoldemAgent Reviews
5/5
TexasHoldemAgent's Main Competitors and alternatives?
- OpenSpiel
- DeepStack
- Libratus
- ACPC frameworks
- PokerRL
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