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

16 February 2021

Chun-Yi Lee

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

20 / 20 papers shown

Title
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid Mikayel Samvelyan Christian Schroeder de Witt Gregory Farquhar Jakob N. Foerster Shimon Whiteson 88 798 0 19 Mar 2020
ROMA: Multi-Agent Reinforcement Learning with Emergent Roles Tonghan Wang Heng Dong V. Lesser Chongjie Zhang 83 218 0 18 Mar 2020
Distributional Reward Decomposition for Reinforcement Learning Zichuan Lin Li Zhao Derek Yang Tao Qin Guangwen Yang Tie-Yan Liu OffRL 38 15 0 06 Nov 2019
Fully Parameterized Quantile Function for Distributional Reinforcement Learning Derek Yang Li Zhao Zichuan Lin Tao Qin Jiang Bian Tie-Yan Liu OOD OffRL 42 136 0 05 Nov 2019
Learning Nearly Decomposable Value Functions Via Communication Minimization Tonghan Wang Jianhao Wang Chongyi Zheng Chongjie Zhang 40 133 0 11 Oct 2019
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control Shanghang Zhang Qi Zhang Jieyu Lin 23 100 0 06 Sep 2019
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning Kyunghwan Son Daewoo Kim Wan Ju Kang D. Hostallero Yung Yi OffRL 52 804 0 14 May 2019
Distributional Reinforcement Learning for Efficient Exploration B. Mavrin Shangtong Zhang Hengshuai Yao Linglong Kong Kaiwen Wu Yaoliang Yu OOD OffRL 47 87 0 13 May 2019
Statistics and Samples in Distributional Reinforcement Learning Mark Rowland Robert Dadashi Saurabh Kumar Rémi Munos Marc G. Bellemare Will Dabney OffRL 51 89 0 21 Feb 2019
The StarCraft Multi-Agent Challenge Mikayel Samvelyan Tabish Rashid Christian Schroeder de Witt Gregory Farquhar Nantas Nardelli Tim G. J. Rudner Chia-Man Hung Philip Torr Jakob N. Foerster Shimon Whiteson 85 950 0 11 Feb 2019
Distributional reinforcement learning with linear function approximation Marc G. Bellemare Nicolas Le Roux Pablo Samuel Castro Subhodeep Moitra 104 23 0 08 Feb 2019
A Comparative Analysis of Expected and Distributional Reinforcement Learning Clare Lyle Pablo Samuel Castro Marc G. Bellemare OffRL 45 81 0 30 Jan 2019
Information-Directed Exploration for Deep Reinforcement Learning Nikolay Nikolov Johannes Kirschner Felix Berkenkamp Andreas Krause 47 70 0 18 Dec 2018
QUOTA: The Quantile Option Architecture for Reinforcement Learning Fengxiang Yang Zhun Zhong Zhiming Luo Sheng Lian Shaozi Li OffRL 45 29 0 05 Nov 2018
Multi-Agent Common Knowledge Reinforcement Learning Christian Schroeder de Witt Jakob N. Foerster Gregory Farquhar Philip Torr Wendelin Bohmer Shimon Whiteson 50 108 0 27 Oct 2018
Implicit Quantile Networks for Distributional Reinforcement Learning Will Dabney Georg Ostrovski David Silver Rémi Munos OffRL 94 531 0 14 Jun 2018
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid Mikayel Samvelyan Christian Schroeder de Witt Gregory Farquhar Jakob N. Foerster Shimon Whiteson 131 1,669 0 30 Mar 2018
Distributional Reinforcement Learning with Quantile Regression Will Dabney Mark Rowland Marc G. Bellemare Rémi Munos 90 757 0 27 Oct 2017
A Distributional Perspective on Reinforcement Learning Marc G. Bellemare Will Dabney Rémi Munos OffRL 93 1,500 0 21 Jul 2017
Value-Decomposition Networks For Cooperative Multi-Agent Learning P. Sunehag Guy Lever A. Gruslys Wojciech M. Czarnecki V. Zambaldi ... Marc Lanctot Nicolas Sonnerat Joel Z Leibo K. Tuyls T. Graepel 67 1,002 0 16 Jun 2017