Anjum48/rl-examples
Examples of published reinforcement learning algorithms in recent literature implemented in TensorFlow
This project offers ready-to-use implementations of advanced reinforcement learning algorithms. It helps machine learning researchers and practitioners experiment with established methods for continuous control problems, such as teaching agents to walk or drive. You provide the problem definition (like a simulated environment), and the project provides the trained agent and performance metrics.
103 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or engineer specifically working with continuous control tasks in reinforcement learning and want to quickly test or benchmark state-of-the-art algorithms.
Not ideal if you are primarily interested in discrete action space problems, such as training agents for Atari games, as these implementations are less tested for such scenarios.
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103
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26
Language
Python
License
MIT
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Last pushed
Aug 03, 2020
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