Fetching the paper…
Reading the bibliography…
Deducing the contribution of each agent and assigning the corresponding reward to them is a crucial problem in cooperative Multi-Agent Reinforcement Learning (MARL).
The starcraft multi-agent challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder De Witt, Gregory Farquhar, Nantas Nardelli, Tim GJ Rudner, Chia-Man Hung, Philip HS Torr, Jakob Foerster, and Shimon Whiteson · 1902
Earlier work this paper cites.
Qtran: Learning to factorize with transformation for cooperative multi-agent reinforcement learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang, David Earl Hostallero, and Yung Yi · 1905
Earlier work this paper cites.
Independent generative adversarial self-imitation learning in cooperative multiagent systems
Xiaotian Hao, Weixun Wang, Jianye Hao, and Yaodong Yang · 1909
Earlier work this paper cites.
Dota 2 with large scale deep reinforcement learning
Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemysław Dȩbiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, et al · 1912
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
Earlier work this paper cites.
An analysis of model-based interval estimation for markov decision processes
Alexander L Strehl and Michael L Littman · 2007
Earlier work this paper cites.
Learning to communicate with deep multi-agent reinforcement learning
Jakob Foerster, Ioannis Alexandros Assael, Nando De Freitas, and Shimon Whiteson · 2016
Earlier work this paper cites.
Deep reinforcement learning: an overview
Seyed Sajad Mousavi, Michael Schukat, and Enda Howley · 2016
Earlier work this paper cites.
A concise introduction to decentralized POMDPs
Frans A Oliehoek and Christopher Amato · 2016
Earlier work this paper cites.
Multi-agent actor-critic for mixed cooperative-competitive environments
Ryan Lowe, Yi I Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, and Igor Mordatch · 2017
Cited alongside, same era.
Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
Cited alongside, same era.
Value-decomposition networks for cooperative multi-agent learning
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinicius Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z Leibo, Karl Tuyls, et al · 2017
Cited alongside, same era.
Counterfactual multi-agent policy gradients
Jakob Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson · 2018
Cited alongside, same era.
Learning attentional communication for multi-agent cooperation
Jiechuan Jiang and Zongqing Lu · 2018
Cited alongside, same era.
Liir: Learning individual intrinsic reward in multi-agent reinforcement learning
Yali Du, Lei Han, Meng Fang, Ji Liu, Tianhong Dai, and Dacheng Tao · 2019
Later among the works it cites.
Actor-attention-critic for multi-agent reinforcement learning
Shariq Iqbal and Fei Sha · 2019
Later among the works it cites.
Human-level performance in 3d multiplayer games with population-based reinforcement learning
Max Jaderberg, Wojciech M Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio Garcia Castaneda, Charles Beattie, Neil C Rabinowitz, Ari S Morcos, Avraham Ruderman, et al · 2019
Later among the works it cites.
Reinforcement learning based speech enhancement for robust speech recognition
Yih-Liang Shen, Chao-Yuan Huang, Syu-Siang Wang, Yu Tsao, Hsin-Min Wang, and Tai-Shih Chi · 2019
Later among the works it cites.
An adaptive deep reinforcement learning approach for mimo pid control of mobile robots
Ignacio Carlucho, Mariano De Paula, and Gerardo G Acosta · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, and Shimon Whiteson · 2018
Cited alongside, same era.
Multi-agent generative adversarial imitation learning
Jiaming Song, Hongyu Ren, Dorsa Sadigh, and Stefano Ermon · 2018
Cited alongside, same era.
Recent trends in deep learning based natural language processing
Tom Young, Devamanyu Hazarika, Soujanya Poria, and Erik Cambria · 2018
Cited alongside, same era.
Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications
Thanh Thi Nguyen, Ngoc Duy Nguyen, and Saeid Nahavandi · 2020
Later among the works it cites.
Influence-based multi-agent exploration
Tonghan Wang*, Jianhao Wang*, Yi Wu, and Chongjie Zhang · 2020
Later among the works it cites.
Generating individual intrinsic reward for cooperative multiagent reinforcement learning
Haolin Wu, Hui Li, Jianwei Zhang, Zhuang Wang, and Jianeng Zhang · 2021
Later among the works it cites.