https://github.com/keon/deep-q-learning

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
https://github.com/keon/deep-q-learning

ddqn deep-learning deep-q-network deep-reinforcement-learning dqn reinforcement-learning

Last synced: 5 months ago
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Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

• Host: GitHub
• URL: https://github.com/keon/deep-q-learning
• Owner: keon
• License: mit
• Archived: true
• Created: 2017-02-06T02:57:42.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-12-04T22:57:25.000Z (over 4 years ago)
• Last Synced: 2024-09-27T04:21:45.027Z (8 months ago)
• Topics: ddqn, deep-learning, deep-q-network, deep-reinforcement-learning, dqn, reinforcement-learning
• Language: Python
• Homepage: https://keon.io/deep-q-learning
• Size: 1.77 MB
• Stars: 1,280
• Watchers: 64
• Forks: 454
• Open Issues: 18
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# deep-q-learning

Introduction to Making a Simple Game AI with Deep Reinforcement Learning

![animation](./assets/animation.gif)

Minimal and Simple Deep Q Learning Implemenation in Keras and Gym. Under 100 lines of code!

The explanation for the `dqn.py` code is covered in the blog article

[https://keon.io/deep-q-learning/](https://keon.io/deep-q-learning/)

I made minor tweaks to this repository such as `load` and `save` functions for convenience.

I also made the `memory` a deque instead of just a list.

This is in order to limit the maximum number of elements in the memory.

The training might be unstable for `dqn.py`. This problem is mitigated in `ddqn.py`.

I'll cover `ddqn` in the next article.