{"total":17,"rows":[{"id":"2106.01969","title":"Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games","created":"2021-06-03","cited_by_count":93,"area":null},{"id":"2110.04184","title":"When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?","created":"2021-10-08","cited_by_count":67,"area":null},{"id":"2202.04129","title":"Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence","created":"2022-02-08","cited_by_count":57,"area":null},{"id":"2110.05707","title":"On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning","created":"2021-10-12","cited_by_count":36,"area":null},{"id":"2205.14590","title":"Independent and Decentralized Learning in Markov Potential Games","created":"2022-05-29","cited_by_count":22,"area":null},{"id":"2310.09727","title":"Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games","created":"2023-10-15","cited_by_count":13,"area":null},{"id":"2206.01880","title":"Learning in Congestion Games with Bandit Feedback","created":"2022-06-04","cited_by_count":10,"area":null},{"id":"2103.09159","title":"Learning to Shape Rewards using a Game of Two Partners","created":"2021-03-16","cited_by_count":9,"area":null},{"id":"2303.04865","title":"Convergence Rates for Localized Actor-Critic in Networked Markov Potential Games","created":"2023-03-08","cited_by_count":9,"area":null},{"id":"2201.12224","title":"Learning Stationary Nash Equilibrium Policies in $n$-Player Stochastic Games with Independent Chains","created":"2022-01-28","cited_by_count":7,"area":null},{"id":"2206.07642","title":"Convergence and Price of Anarchy Guarantees of the Softmax Policy Gradient in Markov Potential Games","created":"2022-06-15","cited_by_count":7,"area":null},{"id":"2208.02204","title":"Efficiently Computing Nash Equilibria in Adversarial Team Markov Games","created":"2022-08-03","cited_by_count":7,"area":null},{"id":"2305.12553","title":"Markov $\\alpha$-Potential Games","created":"2023-05-21","cited_by_count":6,"area":null},{"id":"2206.01451","title":"Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game","created":"2022-06-03","cited_by_count":2,"area":null},{"id":"2312.12067","title":"Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property","created":"2023-12-19","cited_by_count":2,"area":null},{"id":"2308.09902","title":"DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning","created":"2023-08-19","cited_by_count":1,"area":null},{"id":"2312.01587","title":"Scalable and Independent Learning of Nash Equilibrium Policies in $n$-Player Stochastic Games with Unknown Independent Chains","created":"2023-12-04","cited_by_count":1,"area":null}],"next_cursor":null}