{"total":105,"rows":[{"id":"2106.04895","title":"Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning","created":"2021-06-09","cited_by_count":158,"area":"offlinerl"},{"id":"2110.14555","title":"V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL","created":"2021-10-27","cited_by_count":114,"area":null},{"id":"2111.04850","title":"Dueling RL: Reinforcement Learning with Trajectory Preferences","created":"2021-11-08","cited_by_count":106,"area":null},{"id":"2102.04540","title":"Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games","created":"2021-02-08","cited_by_count":69,"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":"2106.02748","title":"Decentralized Q-Learning in Zero-sum Markov Games","created":"2021-06-04","cited_by_count":58,"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":"2204.03991","title":"The Complexity of Markov Equilibrium in Stochastic Games","created":"2022-04-08","cited_by_count":49,"area":null},{"id":"2106.03352","title":"The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces","created":"2021-06-07","cited_by_count":48,"area":null},{"id":"2202.07511","title":"Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets","created":"2022-02-15","cited_by_count":44,"area":null},{"id":"2110.05682","title":"Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games","created":"2021-10-12","cited_by_count":42,"area":null},{"id":"2402.06886","title":"Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF","created":"2024-02-10","cited_by_count":41,"area":"alignment"},{"id":"2102.11494","title":"Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games","created":"2021-02-23","cited_by_count":40,"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":"2107.05216","title":"A Simple Reward-free Approach to Constrained Reinforcement Learning","created":"2021-07-12","cited_by_count":30,"area":null},{"id":"2206.00159","title":"Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus","created":"2022-06-01","cited_by_count":30,"area":"offlinerl"},{"id":"2302.06606","title":"Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation","created":"2023-02-13","cited_by_count":30,"area":null},{"id":"2303.02738","title":"Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback","created":"2023-03-05","cited_by_count":30,"area":null},{"id":"2110.06394","title":"Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation","created":"2021-10-12","cited_by_count":29,"area":null},{"id":"2201.03522","title":"When is Offline Two-Player Zero-Sum Markov Game Solvable?","created":"2022-01-10","cited_by_count":28,"area":null},{"id":"2206.01315","title":"Sample-Efficient Reinforcement Learning of Partially Observable Markov Games","created":"2022-06-02","cited_by_count":27,"area":null},{"id":"2206.10770","title":"On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL","created":"2022-06-21","cited_by_count":27,"area":null},{"id":"2302.03673","title":"Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation","created":"2023-02-07","cited_by_count":27,"area":null},{"id":"2202.01752","title":"Near-Optimal Learning of Extensive-Form Games with Imperfect Information","created":"2022-02-03","cited_by_count":26,"area":null},{"id":"2210.01050","title":"Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games","created":"2022-10-03","cited_by_count":26,"area":null},{"id":"2102.07404","title":"Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games","created":"2021-02-15","cited_by_count":25,"area":null},{"id":"2205.15023","title":"Scalable Multi-Agent Model-Based Reinforcement Learning","created":"2022-05-25","cited_by_count":25,"area":null},{"id":"2112.13521","title":"Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers?","created":"2021-12-27","cited_by_count":24,"area":null},{"id":"2207.14211","title":"Regret Minimization and Convergence to Equilibria in General-sum Markov Games","created":"2022-07-28","cited_by_count":24,"area":null},{"id":"2502.16852","title":"Improving LLM General Preference Alignment via Optimistic Online Mirror Descent","created":"2025-02-24","cited_by_count":24,"area":"alignment"},{"id":"2102.03192","title":"Provably Efficient Algorithms for Multi-Objective Competitive RL","created":"2021-02-05","cited_by_count":22,"area":null},{"id":"2111.11743","title":"Independent Learning in Stochastic Games","created":"2021-11-23","cited_by_count":22,"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":"2106.06279","title":"Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall","created":"2021-06-11","cited_by_count":21,"area":null},{"id":"2110.09771","title":"On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game","created":"2021-10-19","cited_by_count":20,"area":null},{"id":"2305.18258","title":"Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration","created":"2023-05-29","cited_by_count":20,"area":null},{"id":"2302.02571","title":"Offline Learning in Markov Games with General Function Approximation","created":"2023-02-06","cited_by_count":18,"area":"offlinerl"},{"id":"2203.06803","title":"Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits","created":"2022-03-14","cited_by_count":17,"area":null},{"id":"2206.02640","title":"Policy Optimization for Markov Games: Unified Framework and Faster Convergence","created":"2022-06-06","cited_by_count":16,"area":null},{"id":"2210.01907","title":"A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games","created":"2022-10-04","cited_by_count":16,"area":null},{"id":"2208.10458","title":"Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model","created":"2022-08-22","cited_by_count":15,"area":null},{"id":"2303.03100","title":"A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games","created":"2023-03-03","cited_by_count":15,"area":null},{"id":"2304.08944","title":"Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning","created":"2023-04-18","cited_by_count":15,"area":null},{"id":"2105.06029","title":"Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings","created":"2021-05-13","cited_by_count":14,"area":"offlinerl"},{"id":"2110.03244","title":"Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver","created":"2021-10-07","cited_by_count":14,"area":null},{"id":"2203.07322","title":"Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation","created":"2022-03-14","cited_by_count":14,"area":null},{"id":"2209.12430","title":"$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games","created":"2022-09-26","cited_by_count":11,"area":null},{"id":"2212.12567","title":"Adapting to game trees in zero-sum imperfect information games","created":"2022-12-23","cited_by_count":11,"area":null},{"id":"2206.01880","title":"Learning in Congestion Games with Bandit Feedback","created":"2022-06-04","cited_by_count":10,"area":null},{"id":"2307.07670","title":"Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning","created":"2023-07-15","cited_by_count":10,"area":null},{"id":"2307.09470","title":"Multi-Player Zero-Sum Markov Games with Networked Separable Interactions","created":"2023-07-13","cited_by_count":10,"area":null},{"id":"2503.17644","title":"On The Sample Complexity Bounds In Bilevel Reinforcement Learning","created":"2025-03-22","cited_by_count":10,"area":"deeprl"},{"id":"2110.04638","title":"Satisficing Paths and Independent Multi-Agent Reinforcement Learning in Stochastic Games","created":"2021-10-09","cited_by_count":9,"area":null},{"id":"2207.12463","title":"Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions","created":"2022-07-25","cited_by_count":9,"area":null},{"id":"2303.03095","title":"Can We Find Nash Equilibria at a Linear Rate in Markov Games?","created":"2023-03-03","cited_by_count":9,"area":null},{"id":"2207.03902","title":"Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning","created":"2022-07-08","cited_by_count":8,"area":null},{"id":"2302.01477","title":"A Reduction-based Framework for Sequential Decision Making with Delayed Feedback","created":"2023-02-03","cited_by_count":7,"area":null},{"id":"2302.04376","title":"Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning","created":"2023-02-08","cited_by_count":6,"area":null},{"id":"2605.13025","title":"Offline Two-Player Zero-Sum Markov Games with KL Regularization","created":"2026-05-13","cited_by_count":6,"area":null},{"id":"2405.00282","title":"MF-OML: Online Mean-Field Reinforcement Learning with Occupation Measures for Large Population Games","created":"2024-05-01","cited_by_count":5,"area":"deeprl"},{"id":"2602.23116","title":"Provably Efficient Regularized Online RLHF with Generalized Bilinear Preferences","created":"2026-02-26","cited_by_count":5,"area":"alignment"},{"id":"2109.03396","title":"A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent","created":"2021-09-08","cited_by_count":4,"area":null},{"id":"2112.07859","title":"Finite-Sample Analysis of Decentralized Q-Learning for Stochastic Games","created":"2021-12-15","cited_by_count":4,"area":null},{"id":"2201.13170","title":"Cooperative Online Learning in Stochastic and Adversarial MDPs","created":"2022-01-31","cited_by_count":4,"area":null},{"id":"2303.00177","title":"Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation","created":"2023-03-01","cited_by_count":4,"area":null},{"id":"2402.01111","title":"Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints","created":"2024-02-02","cited_by_count":4,"area":"deeprl"},{"id":"2408.10381","title":"Efficient Reinforcement Learning in Probabilistic Reward Machines","created":"2024-08-19","cited_by_count":4,"area":"deeprl"},{"id":"2505.17610","title":"Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning","created":"2025-05-23","cited_by_count":4,"area":"offlinerl"},{"id":"2602.06348","title":"Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret","created":"2026-02-06","cited_by_count":4,"area":null},{"id":"2207.08894","title":"A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games","created":"2022-07-18","cited_by_count":3,"area":null},{"id":"2302.03364","title":"Population-size-Aware Policy Optimization for Mean-Field Games","created":"2023-02-07","cited_by_count":3,"area":null},{"id":"2306.07465","title":"A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning","created":"2023-06-12","cited_by_count":3,"area":null},{"id":"2310.11518","title":"Guarantees for Self-Play in Multiplayer Games via Polymatrix Decomposability","created":"2023-10-17","cited_by_count":3,"area":null},{"id":"2402.07082","title":"Refined Sample Complexity for Markov Games with Independent Linear Function Approximation","created":"2024-02-11","cited_by_count":3,"area":"deeprl"},{"id":"2411.00707","title":"Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms","created":"2024-11-01","cited_by_count":3,"area":null},{"id":"2502.09780","title":"Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games","created":"2025-02-13","cited_by_count":3,"area":null},{"id":"2307.07666","title":"Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty","created":"2023-07-15","cited_by_count":2,"area":null},{"id":"2309.00656","title":"Local and adaptive mirror descents in extensive-form games","created":"2023-09-01","cited_by_count":2,"area":null},{"id":"2404.19292","title":"Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning","created":"2024-04-30","cited_by_count":2,"area":null},{"id":"2508.20315","title":"Multi-Agent Reinforcement Learning in Intelligent Transportation Systems: A Comprehensive Survey","created":"2025-08-27","cited_by_count":2,"area":null},{"id":"2106.07203","title":"Online Sub-Sampling for Reinforcement Learning with General Function Approximation","created":"2021-06-14","cited_by_count":1,"area":null},{"id":"2112.15156","title":"Multi-Agent Reinforcement Learning via Adaptive Kalman Temporal Difference and Successor Representation","created":"2021-12-30","cited_by_count":1,"area":null},{"id":"2208.05363","title":"Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium","created":"2022-08-10","cited_by_count":1,"area":null},{"id":"2211.15792","title":"Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation","created":"2022-11-28","cited_by_count":1,"area":null},{"id":"2310.06243","title":"Sample-Efficient Multi-Agent RL: An Optimization Perspective","created":"2023-10-10","cited_by_count":1,"area":null},{"id":"2403.15045","title":"DP-Dueling: Learning from Preference Feedback without Compromising User Privacy","created":"2024-03-22","cited_by_count":1,"area":null},{"id":"2404.07559","title":"Differentially Private Reinforcement Learning with Self-Play","created":"2024-04-11","cited_by_count":1,"area":"deeprl"},{"id":"2410.09701","title":"Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models","created":"2024-10-13","cited_by_count":1,"area":null},{"id":"2602.07205","title":"Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation","created":"2026-02-06","cited_by_count":1,"area":null},{"id":"2603.20604","title":"Bayesian Learning in Episodic Zero-Sum Games","created":"2026-03-21","cited_by_count":1,"area":"alignment"},{"id":"2609.34656","title":"Minimax Last-Iterate Convergence in Matrix Games with Observed Actions","created":"2026-09-28","cited_by_count":1,"area":null},{"id":"2301.11153","title":"Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning","created":"2023-01-26","cited_by_count":0,"area":null},{"id":"2303.09716","title":"A New Policy Iteration Algorithm For Reinforcement Learning in Zero-Sum Markov Games","created":"2023-03-17","cited_by_count":0,"area":null},{"id":"2308.08858","title":"Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games","created":"2023-08-17","cited_by_count":0,"area":null},{"id":"2403.07890","title":"$\\widetilde{O}(T^{-1})$ Convergence to (Coarse) Correlated Equilibria in Full-Information General-Sum Markov Games","created":"2024-02-02","cited_by_count":0,"area":null},{"id":"2403.11544","title":"RL in Markov Games with Independent Function Approximation: Improved Sample Complexity Bound under the Local Access Model","created":"2024-03-18","cited_by_count":0,"area":null},{"id":"2405.02724","title":"Taming Equilibrium Bias in Risk-Sensitive Multi-Agent Reinforcement Learning","created":"2024-05-04","cited_by_count":0,"area":null},{"id":"2405.03158","title":"Decentralized Online Learning in General-Sum Stackelberg Games","created":"2024-05-06","cited_by_count":0,"area":null},{"id":"2410.18786","title":"Applying Neural Monte Carlo Tree Search to Unsignalized Multi-intersection Scheduling for Autonomous Vehicles","created":"2024-10-24","cited_by_count":0,"area":null},{"id":"2601.12518","title":"Cooperative Multi-agent RL with Communication Constraints","created":"2026-01-18","cited_by_count":0,"area":null}],"next_cursor":"100"}