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RockRL

Reinforcement Learning library for public, for now, it only supports TensorFlow.

Installation

pip install rockrl

Environment requirements

RL algorithms are implemented to support gymnasium==0.29.1 version. Main requirements are that:

env.reset() would return state and info states.
env.step(action) would return state, reward, terminated, truncated, info states.

Supported Algorithms

PPO (Discrete and Continuous)

Code Examples

Proximal Policy Optimization (PPO):

RockRL/tensorflow/examples/ppo/LunarLander-v2/LunarLander-v2.py is an example of using PPO to solve LunarLander-v2 (Discrete) environment.
RockRL/tensorflow/examples/ppo/BipedalWalker-v3/BipedalWalker-v3.py is an example of using PPO to solve BipedalWalker-v2 (Continuous) environment.
RockRL/tensorflow/examples/ppo/BipedalWalkerHardcore-v3/BipedalWalkerHardcore-v3.py is an example of using PPO to solve BipedalWalker-v3 Hardcore (Continuous) environment.

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0.4.6 This release

Jan 30, 2024 2 files

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