Online Learning in Unknown Markov Games

Stochastic games

Lloyd S Shapley · 1953

Earlier work this paper cites.

Markov games as a framework for multi-agent reinforcement learning

Michael L Littman · 1994

Earlier work this paper cites.

Gambling in a rigged casino: The adversarial multi-armed bandit problem

Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire · 1995

Earlier work this paper cites.

Friend-or-foe Q-learning in general-sum games

Michael L Littman · 2001

Earlier work this paper cites.

R-max-a general polynomial time algorithm for near-optimal reinforcement learning

Ronen I Brafman and Moshe Tennenholtz · 2002

Earlier work this paper cites.

Nash Q-learning for general-sum stochastic games

Junling Hu and Michael P Wellman · 2003

Earlier work this paper cites.

Almost optimal model-free reinforcement learning via reference-advantage decomposition

Original

Zihan Zhang, Yuan Zhou, and Xiangyang Ji · 2004

Earlier work this paper cites.

Prediction, learning, and games

Nicolo Cesa-Bianchi and Gábor Lugosi · 2006

Earlier work this paper cites.

Model-based multi-agent rl in zero-sum markov games with near-optimal sample complexity

Original

Kaiqing Zhang, Sham M Kakade, Tamer Başar, and Lin F Yang · 2007

Earlier work this paper cites.

Near-optimal regret bounds for reinforcement learning

Thomas Jaksch, Ronald Ortner, and Peter Auer · 2010

Earlier work this paper cites.

Strategy iteration is strongly polynomial for 2-player turn-based stochastic games with a constant discount factor

Thomas Dueholm Hansen, Peter Bro Miltersen, and Uri Zwick · 2013

Earlier work this paper cites.

Online learning in Markov decision processes with adversarially chosen transition probability distributions

Yasin Abbasi Yadkori, Peter L Bartlett, Varun Kanade, Yevgeny Seldin, and Csaba Szepesvári · 2013

Earlier work this paper cites.

Online learning in episodic Markovian decision processes by relative entropy policy search

Alexander Zimin and Gergely Neu · 2013

Cited alongside, same era.

Markov decision processes: discrete stochastic dynamic programming

Martin L Puterman · 2014

Cited alongside, same era.

Safe, multi-agent, reinforcement learning for autonomous driving

Original

Shai Shalev-Shwartz, Shaked Shammah, and Amnon Shashua · 2016

Cited alongside, same era.

Mastering the game of Go with deep neural networks and tree search

David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016

Cited alongside, same era.

Minimax regret bounds for reinforcement learning

Mohammad Gheshlaghi Azar, Ian Osband, and Rémi Munos · 2017

Cited alongside, same era.

Provably efficient RL with Rich Observations via Latent State Decoding

Simon Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudik, and John Langford · 2019

Later among the works it cites.

Feature-based Q-learning for two-player stochastic games

Original

Zeyu Jia, Lin F Yang, and Mengdi Wang · 2019

Later among the works it cites.

Learning adversarial mdps with bandit feedback and unknown transition

Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, and Tiancheng Yu · 2019

Later among the works it cites.

Online convex optimization in adversarial Markov decision processes

Original

Aviv Rosenberg and Yishay Mansour · 2019

Later among the works it cites.

Grandmaster level in StarCraft II using multi-agent reinforcement learning

Oriol Vinyals, Igor Babuschkin, Wojciech M Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H Choi, Richard Powell, Timo Ewalds, Petko Georgiev, et al · 2019