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

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Categories

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

License

GNU General Public License version 3.0 (GPLv3)

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Additional Project Details

Programming Language

Python

Related Categories

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

Registered

2025-03-13
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