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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
