jaxagents 0.1.12

JAX implementation of Reinforcement Learning agents

Jaxagents

Jaxagents is a Python implementation of Reinforcement Learning agents built upon JAX. The PyPI page of the project can be found here.

Installation

You can install the latest version of jaxagents from PyPI via:

pip install jaxagents

Content

So far, the project includes the following agents:

• Q-learning:
  • Deep Q Networks (DQN)
  • Double Deep Q Networks (DDQN)
  • Categorical Deep Q Networks (often known as C51)
  • Quantile Regression Deep Q Networks (QRDQN)
• Policy gradient:
  • REINFORCE
  • PPO with clipping and GAE

Background

Research and development in Reinforcement Learning can be computationally cumbersome. Utilizing JAX's high computational performance, Jaxagents provides a framework for applying and developing Reinforcement Learning agents that offers benefits in:

• computational speed
• easy control of random number generation
• hyperparameter optimization (via parallelized calculations)