Learning Markov Games with Adversarial Opponents: Efficient Algorithms
and Fundamental Limits

Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits

14 March 2022

Papers citing "Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits"

11 / 11 papers shown

Title
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms Thanh Nguyen-Tang Raman Arora 74 1 0 01 Nov 2024
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games Dylan J. Foster Noah Golowich Sham Kakade 20 10 0 22 Mar 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation Yuanhao Wang Qinghua Liu Yunru Bai Chi Jin 19 28 0 13 Feb 2023
Decentralized model-free reinforcement learning in stochastic games with average-reward objective Romain Cravic Nicolas Gast B. Gaujal 21 2 0 13 Jan 2023
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments Mengxin Yu Zhuoran Yang Jianqing Fan OffRL 13 8 0 23 Aug 2022
Regret Minimization and Convergence to Equilibria in General-sum Markov Games Liad Erez Tal Lancewicki Uri Sherman Tomer Koren Yishay Mansour 36 25 0 28 Jul 2022
A Survey of Decision Making in Adversarial Games Xiuxian Li Min Meng Yiguang Hong Jie-bin Chen AAML 27 12 0 16 Jul 2022
On the Complexity of Adversarial Decision Making Dylan J. Foster Alexander Rakhlin Ayush Sekhari Karthik Sridharan AAML 21 28 0 27 Jun 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang Qinghua Liu Haiquan Wang Caiming Xiong Na Li Yu Bai 13 26 0 06 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu Csaba Szepesvári Chi Jin 26 20 0 02 Jun 2022
Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descent Gabriele Farina Christian Kroer T. Sandholm 46 72 0 28 Jul 2020