XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
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Updated
Sep 17, 2026 - Python
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
PyTorch implements multi-agent reinforcement learning algorithms, including QMIX, Independent PPO, Centralized PPO, Grid Wise Control, Grid Wise Control+PPO, Grid Wise Control+DDPG.
StarCraft II Multi Agent Challenge : QMIX, COMA, LIIR, QTRAN, Central V, ROMA, RODE, DOP, Graph MIX
PPO and PyMARL baseline for Pogema environment
Source code for the MARL-enabled real-time control of urban drainage system
QMIX implemented in TensorFlow 2
Continual Multi-agent Reinforcement Learning in Dynamic Environments
Scalable Multi-Agent Reinforcement Learning with IQL and QMIX — from-scratch implementation in a custom grid environment. Compare independent vs centralized learning as agents scale from 2 to 10.
Integrated supply chain intelligence platform for disruption detection, demand forecasting, resource allocation, and route optimization using GNNs, TFT, MARL, and POMO.
POMDP cat-and-mouse PettingZoo grid world with recurrent MARL baselines, diagnostics, and demo assets.
JaxMARL-based MARL benchmark: RNN vs Transformer vs SSM backbones for QMIX, evaluated on Hanabi, MPE, and SMAX.
MAPPO experiments with VDN- and QMIX-style value factorisation
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