Texas Hold'em AI 🤖

CS Independent Study @UVa

Overview

This is an independent study on the application of current machine learning techniques into Texas Hold’em AI.

Setup

• TensorFlow documentation

  # Ubuntu/Linux 64-bit
  $ sudo apt-get install python-pip python-dev
  # Ubuntu/Linux 64-bit, CPU only, Python 3.5
  $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0-cp35-cp35m-linux_x86_64.whl
  
  # Mac OS X
  $ sudo easy_install pip3
  $ sudo easy_install --upgrade six
  # Mac OS X, CPU only, Python 3.4 or 3.5:
  $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow-0.11.0-py3-none-any.whl
  
  
  $ sudo pip3 install --upgrade $TF_BINARY_URL

  • Troubleshoot

• Jupyter Notebook documentation

  $ pip3 install --upgrade pip
  $ pip3 install jupyter
  $ jupyter notebook

Demo

Timeline

Resources

• Machine Learning
  • Framework
    • Awesome TensorFlow Link
    • TensorFlow Playground Link
    • Binary Stochastic Neurons in Tensorflow Link
  • Relavant Reports
    • End of Code by Wired
    • Why Randomness is Important for Deep Learning Link
  • Book
    • Neural Networks and Deep Learning Link
  • Research Paper
    • Deep Reinforcement Learning from Self-Play in Imperfect-Information Games PDF
    • Mastering the Game of Go with Deep Neural Networks and Tree Search PDF
• Game Theory
  • prisoner dilemma game Link
• Behavior Theory
• Poker Strategy
  • the Poker Bank link
• Related Course
  • CS221: Artificial Intelligence
  • CS6316 Machine Learning
  • CS6501 Poker
  • AI Strategies for Solving Poker Texas Hold'em Slides
• Others' work
  • Claudico Overview
  • Slumbot
  • DeepStack

Acknowledge

Thanks Prof. David Evans for the instructions and supports.

Contact Us

• Current Collaborators
  • Charlie Wu jw7jb@virginia.edu
  • Tong Qiu tq7bw@virginia.edu