MLPro-Int-Gymnasium - Integration between Gymnasium and MLPro

Welcome to MLPro-Int-Gymnasium, an extension to MLPro to integrate the Gymnasium package. MLPro is a middleware framework for standardized machine learning in Python. It is developed by the South Westphalia University of Applied Sciences, Germany, and provides standards, templates, and processes for hybrid machine learning applications. Gymnasium, in turn, provides a diverse suite of reinforcement learning environments.

MLPro-Int-Gymnasium offers wrapper classes that allow the reuse of environments from Gymnasium in MLPro, or the other way around.

Preparation

Before running the examples, please install the latest versions of MLPro, Gymnasium, and MLPro-Int-Gymnasium as follows:

pip install mlpro-int-gymnasium[full] --upgrade

See also

• MLPro - Machine Learning Professional

• MLPro-RL - Sub-framework for reinforcement learning

• Gymnasium - An API standard for reinforcement learning with a diverse collection of reference environments

• Further MLPro extensions

• MLPro-Int-Gymnasium on GitHub

Example Pool

• Reinforcement Learning
  • Howto RL-AGENT-001: Run an Agent with Own Policy on Gym Environment
  • Howto RL-AGENT-002: Train an Agent with Own Policy on Gym Environment
  • Howto RL-AGENT-003: Run Multi-Agent with Own Policy on Gym Environment
  • Howto RL-AGENT-004: Train Multi-Agent with Own Policy on Gym Environment
  • Howto RL-WP-001: MLPro Environment to Gymnasium Environment
  • Howto RL-WP-002: Gymnasium Environment to MLPro Environment
• Dynamic Games in Game Theory
  • Howto GT-DG-001: Run Multi-Player with Own Policy on Gym Environment
  • Howto GT-DG-002: Train Multi-Player with Own Policy on Gym Environment

API Reference

• Wrapper Root Class
  • WrEnvGYM2MLPro
  • WrEnvMLPro2GYM
• Environments
  • Multi Cartpole
• Game Boards
  • Multi Cartpole

About

• Release Notes
• Disclaimer
  • Disclaimers for MLPro Usage
  • Consent