GitHub / proroklab / VectorizedMultiAgentSimulator
VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/proroklab%2FVectorizedMultiAgentSimulator
Stars: 411
Forks: 81
Open issues: 8
License: gpl-3.0
Language: Python
Size: 4.81 MB
Dependencies parsed at: Pending
Created at: almost 3 years ago
Updated at: 3 days ago
Pushed at: 3 days ago
Last synced at: 3 days ago
Commit Stats
Commits: 482
Authors: 11
Mean commits per author: 43.82
Development Distribution Score: 0.257
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/proroklab/VectorizedMultiAgentSimulator
Topics: gym, gym-environment, marl, multi-agent, multi-agent-learning, multi-agent-reinforcement-learning, multi-agent-simulation, multi-agent-systems, multi-robot, multi-robot-framework, multi-robot-sim, multi-robot-simulator, multi-robot-systems, pytorch, rllib, robotics, simulation, simulator, vectorization, vectorized