Neuron_poker

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Neuron Poker is an open-source Texas Hold'em OpenAI Gym environment for reinforcement learning, built with Keras-RL. It includes virtual rendering and Monte Carlo for equity calculation, allowing users to train neural networks to play poker.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is neuron_poker?

Neuron Poker provides an open-source OpenAI Gym environment specifically designed for training neural networks to play Texas Hold'em poker. Leveraging Keras-RL for deep reinforcement learning, this tool offers features like virtual rendering to visualize gameplay and Monte Carlo simulations for accurate equity calculation. It supports various agent types, including random, keypress-controlled, equity-based, and Deep Q learning agents. The environment is highly customizable, allowing users to add their own player models and collaborate through pull requests. Advanced users can integrate a C++ version of the equity calculator for significantly faster computations, making it an ideal platform for AI researchers and developers focused on poker AI.

Best used for

Ideal for developers and data scientists who need to train AI agents to play Texas Hold'em poker, experiment with various reinforcement learning algorithms, and evaluate different poker strategies. Especially valuable for those looking for an open-source, customizable environment with fast equity calculation capabilities.

Common actions

train AI agents

simulate poker games

develop reinforcement learning models

evaluate poker strategies

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Capabilities

Key features

Texas Hold'em environment
Reinforcement learning (Keras-RL)
Virtual rendering
Monte Carlo equity calculation
C++ equity calculator
Customizable AI agents

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What programming languages are primarily used in Neuron Poker?

Neuron Poker is primarily developed using Python, with significant components in Cython and C++ for performance-critical tasks like the equity calculator. This blend allows for flexible development in Python while leveraging the speed of C++ where needed.

Can I contribute my own AI poker agent to Neuron Poker?

Yes, Neuron Poker is designed for collaboration. You can develop your own player models and submit them via a pull request on GitHub. The project encourages community contributions to create more sophisticated poker-playing AI agents.

Does Neuron Poker support different types of AI agents?

Yes, the environment supports various agent types, including random decision-making agents, agents controlled by keypress, equity-aware agents, and Deep Q learning agents based on Keras-RL. Users can also implement and integrate their custom reinforcement learning models.

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AI Agents & Automation › AI Frameworks & Infra AI Agents & Automation › General-Purpose Agents

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