multiagent_mujoco
Basic Information
This repository is a public benchmark for continuous multi-agent robotic control built on OpenAI's MuJoCo Gym environments. It aims to provide a common set of simulated tasks and scenarios for evaluating continuous control algorithms in multi-agent settings. The project focuses on simulation-based benchmarking rather than hardware deployment and is intended to support reproducible comparisons across controllers, coordination strategies, and learning algorithms. The GitHub project includes a main README reference in its file tree and has attracted community attention as indicated by stars and forks. The repo serves as a centralized resource for researchers and developers who need standardized multi-agent continuous control tasks under the MuJoCo/Gym simulation framework.