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ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments that support the subset of OpenAI Gym's interface (reset and step methods) can be used.
Features
- ChainerRL is tested with 3.6
- ChainerRL can be installed via PyPI
- It can also be installed from the source code
- You can try ChainerRL Quickstart Guide first, or check the examples ready for Atari 2600 and Open AI Gym
- Following algorithms have been implemented in ChainerRL
- ChainerRL has a set of accompanying visualization tools
Project Samples
Categories
Libraries, Machine Learning, Deep Learning Frameworks, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
MIT LicenseFollow ChainerRL
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