miyosuda/async_deep_reinforce
Asynchronous Methods for Deep Reinforcement Learning
This project helps machine learning researchers or students explore advanced reinforcement learning techniques. It takes game environment data and, through training, produces an AI agent capable of playing games like Atari Pong. This is ideal for those studying or reproducing cutting-edge AI research.
591 stars. No commits in the last 6 months.
Use this if you are a researcher or student working with deep reinforcement learning and want to implement or understand the Asynchronous Advantage Actor-Critic (A3C) method.
Not ideal if you are looking for a pre-trained game-playing AI or a general-purpose reinforcement learning library for diverse applications beyond reproducing specific research.
Stars
591
Forks
189
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 09, 2018
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