TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	REMOVE

QPLEX: Duplex Dueling Multi-Agent Q-Learning

ICLR 2021 • Jianhao Wang • Zhizhou Ren • Terry Liu • Yang Yu • Chongjie Zhang

We explore value-based multi-agent reinforcement learning (MARL) in the popular paradigm of centralized training with decentralized execution (CTDE). CTDE has an important concept, Individual-Global-Max (IGM) principle, which requires the consistency between joint and local action selections to support efficient local decision-making... (read more)

PDF Abstract ICLR 2021 PDF ICLR 2021 Abstract

Code

Add Remove Mark official

oxwhirl/wqmix

Tasks

Add Remove

DECISION MAKING

MULTI-AGENT REINFORCEMENT LEARNING

Q-LEARNING

STARCRAFT

STARCRAFT II

Datasets

MuJoCo

Arcade Learning Environment

D4RL

Results from the Paper

Edit

Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

Add Remove

METHOD	TYPE
Dense Connections	Feedforward Networks
Double Q-learning	Off-Policy TD Control
Q-Learning	Off-Policy TD Control
Convolution	Convolutions
Dueling Network	Q-Learning Networks

QPLEX: Duplex Dueling Multi-Agent Q-Learning

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Datasets Edit

Results from the Paper Edit

Methods used in the Paper Edit Add Remove

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Edit

Methods used in the Paper

Add Remove