XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

Concise pytorch implements of MARL algorithms, including MAPPO, MADDPG, MATD3, QMIX and VDN.

implementation of MADDPG using PyTorch and multiagent-particle-envs

Minimal path extraction using the fast marching method

Load microtonal split-key mappings on a ROLI Seaboard RISE/Block

A modern implementation of MADDPG and MADDPG-Approx algorithms using PyTorch and PettingZoo environments. This project provides a clean, modular framework for multi-agent reinforcement learning research, featuring parallel training capabilities, comprehensive visualization tools, and support for various cooperative and competitive scenarios

This repository contains code to train and test policies for a MPE environment (Simple Spread). Training is done using DQL for independent learning. Testing was done using 3 different policies: RL, Simple Policy, Complex Policy.

Implementation of a simple linear regression with single feature