Provably Efficient Fictitious Play Policy Optimization for Zero-Sum
Markov Games with Structured Transitions

Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions

International Conference on Machine Learning (ICML), 2022

25 July 2022

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Papers citing "Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions"

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Title
Risk Sensitivity in Markov Games and Multi-Agent Reinforcement Learning: A Systematic Review Hafez Ghaemi Shirin Jamshidi Mohammad Mashreghi M. N. Ahmadabadi Hamed Kebriaei 255 1 0 10 Jun 2024
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning Qiaosheng Zhang Chenjia Bai Shuyue Hu Zhen Wang Xuelong Li 223 2 0 30 Apr 2024
Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games Hafez Ghaemi Hamed Kebriaei Alireza Ramezani Moghaddam Majid Nili Ahamadabadi 218 2 0 08 Feb 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property Ioannis Anagnostides Ioannis Panageas Gabriele Farina Tuomas Sandholm 276 3 0 19 Dec 2023
Scalable and Independent Learning of Nash Equilibrium Policies in $n$ -Player Stochastic Games with Unknown Independent Chains Tiancheng Qin S. Rasoul Etesami 259 2 0 04 Dec 2023
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash EquilibriaNeural Information Processing Systems (NeurIPS), 2023 Fivos Kalogiannis Ioannis Panageas 272 8 0 23 May 2023
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter ConvergenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 S. Pattathil Jianchao Tan Asuman Ozdaglar 275 14 0 23 Oct 2022
Learning Stationary Nash Equilibrium Policies in $n$ -Player Stochastic Games with Independent ChainsSIAM Journal of Control and Optimization (SICON), 2022 S. Rasoul Etesami 334 9 0 28 Jan 2022