GENiALi/RockRL

Reinforcement Learning library for public

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.