DFAC Framework: Factorizing the Value Function via Quantile Mixture for
Multi-Agent Distributional Q-Learning

DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning

16 February 2021

Cheng-Kuang Lee

Chun-Yi Lee

Papers citing "DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning"

9 / 9 papers shown

Title
Foundations of Multivariate Distributional Reinforcement Learning Harley Wiltzer Jesse Farebrother A. Gretton Mark Rowland OffRL 35 2 0 31 Aug 2024
Multi-agent Reinforcement Learning: A Comprehensive Survey Dom Huh Prasant Mohapatra AI4CE 30 8 0 15 Dec 2023
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning Ji-Yun Oh Joonkee Kim Minchan Jeong Se-Young Yun 27 1 0 03 Mar 2023
Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative Multi-Agent Reinforcement Learning Zhiwei Xu Bin Zhang Dapeng Li Guangchong Zhou Zeren Zhang Guoliang Fan 28 3 0 04 Feb 2023
Learning Generalizable Risk-Sensitive Policies to Coordinate in Decentralized Multi-Agent General-Sum Games Ziyi Liu Xian Guo Yongchun Fang 18 0 0 31 May 2022
Divergence-Regularized Multi-Agent Actor-Critic Kefan Su Zongqing Lu 46 25 0 01 Oct 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 30 92 0 14 Sep 2021
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization Jianhao Wang Zhizhou Ren Beining Han Jianing Ye Chongjie Zhang OffRL 21 32 0 31 May 2020
ROMA: Multi-Agent Reinforcement Learning with Emergent Roles Tonghan Wang Heng Dong V. Lesser Chongjie Zhang 55 210 0 18 Mar 2020