VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently.

Features

  • Highly optimized for vectorized multi-agent simulation to run thousands of agents in parallel
  • Supports physics-based interactions and dynamic environments
  • Enables large-scale reinforcement learning experiments with efficient state and action management
  • Easily customizable agent behavior and environment dynamics
  • Includes built-in visualization tools for monitoring agent interactions

Project Samples

VectorizedMultiAgentSimulator (VMAS) Screenshot 1

Project Activity

See All Activity >

Categories

Multi-Agent Systems, Multi-Agent Frameworks, Reinforcement Learning Frameworks

License

GNU General Public License version 3.0 (GPLv3)

Follow VectorizedMultiAgentSimulator (VMAS)

VectorizedMultiAgentSimulator (VMAS) Web Site

Other Useful Business Software
MongoDB Atlas runs apps anywhere Icon
MongoDB Atlas runs apps anywhere

Deploy in 115+ regions with the modern database for every enterprise.

MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of VectorizedMultiAgentSimulator (VMAS)!

Additional Project Details

Programming Language

Python

Related Categories

Python Multi-Agent Systems, Python Multi-Agent Frameworks, Python Reinforcement Learning Frameworks

Registered

2025-03-13
Report inappropriate content