Max van Dijck 232c331ce3 [RLlib] Rename all np.product usage to np.prod (#46317) 3 月之前
..
examples 5f25de5d48 [RLlib-contrib] QMIX. (#36682) 1 年之前
src 5f25de5d48 [RLlib-contrib] QMIX. (#36682) 1 年之前
tests 5f25de5d48 [RLlib-contrib] QMIX. (#36682) 1 年之前
tuned_examples a9ac55d4f2 [RLlib; RLlib contrib] Move `tuned_examples` into rllib_contrib and remove CI learning tests for contrib algos. (#40444) 1 年之前
BUILD a9ac55d4f2 [RLlib; RLlib contrib] Move `tuned_examples` into rllib_contrib and remove CI learning tests for contrib algos. (#40444) 1 年之前
README.md 5f25de5d48 [RLlib-contrib] QMIX. (#36682) 1 年之前
pyproject.toml 232c331ce3 [RLlib] Rename all np.product usage to np.prod (#46317) 3 月之前
requirements.txt 232c331ce3 [RLlib] Rename all np.product usage to np.prod (#46317) 3 月之前

README.md

QMIX (Monotonic Value Function Factorisation for Multi-Agent RL)

QMIX Q-Mix is a specialized multi-agent algorithm. Code here is adapted from https://github.com/oxwhirl/pymarl_alpha to integrate with RLlib multi-agent APIs. To use Q-Mix, you must specify an agent grouping in the environment (see the two-step game example). Currently, all agents in the group must be homogeneous. The algorithm can be scaled by increasing the number of workers or using Ape-X.

Installation

conda create -n rllib-qmix python=3.10
conda activate rllib-qmix
pip install -r requirements.txt
pip install -e '.[development]'

Usage

[QMIX Example]()