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Concise pytorch implements of MARL algorithms, including MAPPO, MADDPG, MATD3, QMIX and VDN.
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
Multi-agent project (commnet, bicnet, maddpg) in pytorch for Multi-Agent Particle Environment
Distributed Multi-Agent Cooperation Algorithm based on MADDPG with prioritized batch data.
MARLToolkit: The Multi-Agent Rainforcement Learning Toolkit. Include implementation of MAPPO, MADDPG, QMIX, VDN, COMA, IPPO, QTRAN, MAT...
implementation of MADDPG using PettingZoo and PyTorch
This is a reinforcement learning algorithm library. The code takes into account both performance and simplicity, with little dependence.
Code for the RL method MATD3 described in the paper "Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics"
Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG
Project on multi agent reinforcement learning applied on patrolling agents
implementation of MADDPG using PyTorch and multiagent-particle-envs
This is Multi agent deep reinforcement learning repo which trains an agent to play Tennis. It trains by playing against itself.
Implementation Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm in keras
RLToolkit is a flexible and high-efficient reinforcement learning framework. Include implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
This repository contains the implementation of deep reinforcement learning algorithms to solve various unity The Environments.
Multi-Agent Deep Deterministic Policy Gradient implementation with pytorch
Repository for the Udacity Deep Reinforcement Learning Nanodegree
Tennis Game play using Multi Agent DDPG - Deep Reinforcement Learning
My solution to Collaboration and Competition using MADDPG algorithm, Udacity 3rd project of Deep RL Nanodegree from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Developed a Multi-Agent DDPG to solve Vehicle Scheduling problem.
In this repo, I implement deep deterministic policy gradients and multi-agent deep deterministic poilicy gradients to solve the Tennis enironment (Unity ML-Agents)
In box2d environment, complete the laser shooting battle of car 1v1 and 2v2 through the method of deep reinforcement learning.
Multi-Agent Reinforcement Learning: Collaboration and Competition
Comparing Exploitation-Based and Game Theory Optimal Based Approaches in a Multi-Agent Environment (2020 Spring)
Multi-agent DDPG on ml-agents environment
Some model free RL algorithms
Experimenting with Policy Gradient Reinforcement Learning Algorithms and Evolutionary Strategies in a warehouse congestion-management domain.
This Repository Contains PyTorch Implementation of Multi Agent DDPG Algorithm to train agents to play tennis.
Implementation of project 3 for Udacity's Deep Reinforcement Learning Nanodegree
Build and test DRL algorithms in different environments
Computational framework for reinforcement learning in traffic control
Learn how to apply reinforcement learning methods to applications that involve multiple, interacting agents. These techniques are used in a variety of applications, such as the coordination of autonomous vehicles.