A set of communication-oriented environments

Multi Particle Environments 2 (MPE2) is collection of environments where particle agents can (sometimes) move, communicate, see each other, push each other around, and interact with fixed landmarks.

These environments are originally from OpenAI’s MPE codebase, with several minor fixes, mostly related to making the action space discrete by default, making the rewards consistent and cleaning up the observation space of certain environments. MPE2 additionally includes 3 new environments.

Installation

The unique dependencies for this set of environments can be installed via:

pip install mpe2

Example

To launch a Simple Push environment with random agents:

from mpe2 import simple_push_v3

env = simple_push_v3.env(render_mode="human")
env.reset(seed=42)

for agent in env.agent_iter():
    observation, reward, termination, truncation, info = env.last()

    if termination or truncation:
        action = None
    else:
        # this is where you would insert your policy
        action = env.action_space(agent).sample()

    env.step(action)
    
env.close()

Citation

The MPE environments were originally described in the following work:

@article{mordatch2017emergence,
  title={Emergence of Grounded Compositional Language in Multi-Agent Populations},
  author={Mordatch, Igor and Abbeel, Pieter},
  journal={arXiv preprint arXiv:1703.04908},
  year={2017}
}

But were first released as a part of this work:

@article{lowe2017multi,
  title={Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments},
  author={Lowe, Ryan and Wu, Yi and Tamar, Aviv and Harb, Jean and Abbeel, Pieter and Mordatch, Igor},
  journal={Neural Information Processing Systems (NIPS)},
  year={2017}
}

Please cite one or both of these if you use these environments in your research.