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A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

Vectorizedmultiagentsimulator ⭐ 210

VMAS is a vectorized framework 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.

Benchmarl ⭐ 115

A collection of MARL benchmarks based on TorchRL

This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.

Multi Agent Reinforcement Learning ⭐ 20

Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG

Multi Agent Ddpg Using Pttorch And Ml Agents ⭐ 11

A simple example of how to implement vector based DDPG for MARL tasks using PyTorch and a ML-Agents environment.

Dynamic Coverage Control ⭐ 6

毕业设计 - 连通保持约束下的无人机动态覆盖控制

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