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Research platform for Human-in-the-loop learning & Multi-Agent Reinforcement Learning

Start building & training agents with HILL and MARL techniques within Gym, Petting Zoo, and more...

Video Demo

Key features

Cogment Verse is a SDK helping researchers and developers in the fields of human-in-the-loop learning (HILL) and multi-agent reinforcement learning (MARL) train and validate their agents at scale. Cogment Verse instantiates the open-source Cogment platform for environments following the OpenAI Gym mold, making it easy to get started.

Simply clone the repo and start training.

Atari Double Dunk - From Petting ZooGo - From Petting ZooAtari Montezuma's Revenge - From Open AI GymLunar Lander - From Open AI Gym

HILL and MARL Training

Our SDK includes base implementations for multiple RL algorithms such as DQN, TD3, A2C and PPO for both single- and multi-agent reinforcement learning (MARL). For human-in-the-loop learning, Cogment Verse includes different paradigms like learning from demonstrations (behavior cloning), learning from human interventions, and learning from explicit human feedback (RLHF). More importantly, the SDK makes it easy to implement any asynchronous centralized training / decentralized execution algorithm.

Interactive Web Application

A built-in interactive web application enables seamless human participation in episodes during the training and validation processes. Additional environments can be made interactive with very little web development required..

Collaboration Patterns

Library of predefined roles for agents or humans facilitating the implementation of multiple collaboration patterns: co-players, teacher/student dual control, evaluators, etc.

Extensive Environment Library

The existing environment library includes the standard OpenAI Gym environments as well as board games, card games, and other multi-agent environments from Petting Zoo. Other environments are gradually being added, such as Isaac Gym or Overcooked-AI. Implementing your own interactive custom environments is also quite straightforward.

Experiments Management

Monitor and manage reproducible experiments, thanks to:


If you use Cogment Verse in your research, please cite our demo paper appearing in AAMAS 2023 proceedings:

  title={Hiking up that HILL with Cogment-Verse: Train \& Operate Multi-agent Systems Learning from Humans},
  author={Gottipati, Sai Krishna and Nguyen, Luong-Ha and Mars, Clod{\'e}ric and Taylor, Matthew E},
  booktitle={Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},