{"total":133,"rows":[{"id":"2206.15378","title":"Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning","created":"2022-06-30","cited_by_count":131,"area":null},{"id":"2212.07489","title":"SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning","created":"2022-12-14","cited_by_count":122,"area":null},{"id":"2107.06857","title":"Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot","created":"2021-07-14","cited_by_count":99,"area":null},{"id":"2106.06135","title":"DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning","created":"2021-06-11","cited_by_count":66,"area":null},{"id":"2206.05825","title":"A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games","created":"2022-06-12","cited_by_count":66,"area":null},{"id":"2104.03113","title":"Scaling Scaling Laws with Board Games","created":"2021-04-07","cited_by_count":63,"area":null},{"id":"2306.00577","title":"TorchRL: A data-driven decision-making library for PyTorch","created":"2023-06-01","cited_by_count":60,"area":null},{"id":"2306.09884","title":"Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX","created":"2023-06-16","cited_by_count":58,"area":null},{"id":"2104.06159","title":"Muesli: Combining Improvements in Policy Optimization","created":"2021-04-13","cited_by_count":53,"area":null},{"id":"2303.17503","title":"Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learning","created":"2023-03-29","cited_by_count":51,"area":null},{"id":"2203.11973","title":"Scalable Deep Reinforcement Learning Algorithms for Mean Field Games","created":"2022-03-22","cited_by_count":38,"area":null},{"id":"2110.14771","title":"ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets","created":"2021-10-27","cited_by_count":36,"area":null},{"id":"2103.06426","title":"XDO: A Double Oracle Algorithm for Extensive-Form Games","created":"2021-03-11","cited_by_count":34,"area":null},{"id":"2402.01704","title":"Steering Language Models with Game-Theoretic Solvers","created":"2024-01-24","cited_by_count":28,"area":null},{"id":"2404.18909","title":"Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty","created":"2024-04-29","cited_by_count":25,"area":null},{"id":"2206.04122","title":"ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret","created":"2022-06-08","cited_by_count":24,"area":null},{"id":"2106.07551","title":"MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning","created":"2021-06-05","cited_by_count":23,"area":null},{"id":"2112.03178","title":"Student of Games: A unified learning algorithm for both perfect and imperfect information games","created":"2021-12-06","cited_by_count":23,"area":null},{"id":"2106.09435","title":"Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers","created":"2021-06-17","cited_by_count":21,"area":null},{"id":"2106.12928","title":"Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality","created":"2021-06-24","cited_by_count":21,"area":null},{"id":"2103.07780","title":"Online Double Oracle","created":"2021-03-13","cited_by_count":18,"area":null},{"id":"2205.13746","title":"Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games","created":"2022-05-27","cited_by_count":18,"area":null},{"id":"2101.04237","title":"Solving Common-Payoff Games with Approximate Policy Iteration","created":"2021-01-11","cited_by_count":15,"area":null},{"id":"2102.06973","title":"Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games","created":"2021-02-13","cited_by_count":15,"area":null},{"id":"2304.13269","title":"Games for Artificial Intelligence Research: A Review and Perspectives","created":"2023-04-26","cited_by_count":14,"area":null},{"id":"2310.11305","title":"MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games","created":"2023-10-17","cited_by_count":14,"area":null},{"id":"2407.00401","title":"PUZZLES: A Benchmark for Neural Algorithmic Reasoning","created":"2024-06-29","cited_by_count":13,"area":null},{"id":"2103.04539","title":"Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games","created":"2021-03-08","cited_by_count":12,"area":null},{"id":"2203.04735","title":"A Survey on Reinforcement Learning Methods in Character Animation","created":"2022-03-07","cited_by_count":12,"area":null},{"id":"2207.06541","title":"Self-Play PSRO: Toward Optimal Populations in Two-Player Zero-Sum Games","created":"2022-07-13","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":"2302.06064","title":"Provably Safe Reinforcement Learning with Step-wise Violation Constraints","created":"2023-02-13","cited_by_count":11,"area":null},{"id":"2110.11737","title":"Measuring the Non-Transitivity in Chess","created":"2021-10-22","cited_by_count":10,"area":null},{"id":"2403.02227","title":"Policy Space Response Oracles: A Survey","created":"2024-03-04","cited_by_count":10,"area":null},{"id":"2201.07700","title":"Anytime PSRO for Two-Player Zero-Sum Games","created":"2022-01-19","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":"2204.00302","title":"Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes","created":"2022-04-01","cited_by_count":8,"area":null},{"id":"2205.15879","title":"Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games","created":"2022-05-31","cited_by_count":8,"area":null},{"id":"2210.14640","title":"HSVI can solve zero-sum Partially Observable Stochastic Games","created":"2022-10-26","cited_by_count":8,"area":null},{"id":"2503.14576","title":"SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas","created":"2025-03-18","cited_by_count":8,"area":null},{"id":"2101.09562","title":"Deep Learning for General Game Playing with Ludii and Polygames","created":"2021-01-23","cited_by_count":7,"area":null},{"id":"2110.04961","title":"Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent","created":"2021-10-11","cited_by_count":7,"area":null},{"id":"2206.09161","title":"A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving","created":"2022-06-18","cited_by_count":7,"area":null},{"id":"2305.17342","title":"Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL","created":"2023-05-27","cited_by_count":7,"area":null},{"id":"2310.07745","title":"Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey","created":"2023-10-11","cited_by_count":7,"area":null},{"id":"2412.11979","title":"AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws","created":"2024-12-16","cited_by_count":7,"area":null},{"id":"2102.13243","title":"Swift for TensorFlow: A portable, flexible platform for deep learning","created":"2021-02-26","cited_by_count":6,"area":null},{"id":"2208.10138","title":"Learning Correlated Equilibria in Mean-Field Games","created":"2022-08-22","cited_by_count":6,"area":null},{"id":"2302.00797","title":"Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning","created":"2023-02-01","cited_by_count":6,"area":null},{"id":"2407.16312","title":"MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning","created":"2024-07-23","cited_by_count":6,"area":null},{"id":"2112.11731","title":"Graph augmented Deep Reinforcement Learning in the GameRLand3D environment","created":"2021-12-22","cited_by_count":5,"area":null},{"id":"2210.06012","title":"Phantom -- A RL-driven multi-agent framework to model complex systems","created":"2022-10-12","cited_by_count":5,"area":null},{"id":"2303.03196","title":"Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning","created":"2023-03-02","cited_by_count":5,"area":null},{"id":"2304.01547","title":"Regularization of the policy updates for stabilizing Mean Field Games","created":"2023-04-04","cited_by_count":5,"area":null},{"id":"2412.19873","title":"Minimax-Optimal Multi-Agent Robust Reinforcement Learning","created":"2024-12-27","cited_by_count":5,"area":null},{"id":"2101.12639","title":"Optimizing $\\alpha\\mu$","created":"2021-01-29","cited_by_count":4,"area":null},{"id":"2112.03636","title":"Godot Reinforcement Learning Agents","created":"2021-12-07","cited_by_count":4,"area":null},{"id":"2201.10377","title":"Public Information Representation for Adversarial Team Games","created":"2022-01-25","cited_by_count":4,"area":null},{"id":"2206.08851","title":"SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments","created":"2022-06-17","cited_by_count":4,"area":null},{"id":"2212.00253","title":"Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox","created":"2022-12-01","cited_by_count":4,"area":null},{"id":"2401.05133","title":"Neural Population Learning beyond Symmetric Zero-sum Games","created":"2024-01-10","cited_by_count":4,"area":null},{"id":"2602.16928","title":"Discovering Multiagent Learning Algorithms with Large Language Models","created":"2026-02-18","cited_by_count":4,"area":null},{"id":"2609.19134","title":"ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments","created":"2026-09-16","cited_by_count":4,"area":null},{"id":"2112.00940","title":"Reward-Free Attacks in Multi-Agent Reinforcement Learning","created":"2021-12-02","cited_by_count":3,"area":null},{"id":"2204.02785","title":"Reinforcement Learning Agents in Colonel Blotto","created":"2022-04-04","cited_by_count":3,"area":null},{"id":"2205.12787","title":"Impartial Games: A Challenge for Reinforcement Learning","created":"2022-05-25","cited_by_count":3,"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":"2210.02205","title":"Game Theoretic Rating in N-player general-sum games with Equilibria","created":"2022-10-05","cited_by_count":3,"area":null},{"id":"2302.12359","title":"Targeted Search Control in AlphaZero for Effective Policy Improvement","created":"2023-02-23","cited_by_count":3,"area":null},{"id":"2302.12676","title":"Towards Computationally Efficient Responsibility Attribution in Decentralized Partially Observable MDPs","created":"2023-02-24","cited_by_count":3,"area":null},{"id":"2304.13138","title":"The Update-Equivalence Framework for Decision-Time Planning","created":"2023-04-25","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":"2407.20351","title":"LiteEFG: An Efficient Python Library for Solving Extensive-form Games","created":"2024-07-29","cited_by_count":3,"area":null},{"id":"2410.16600","title":"Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning","created":"2024-10-22","cited_by_count":3,"area":null},{"id":"2103.00187","title":"Multi-agent Reinforcement Learning in OpenSpiel: A Reproduction Report","created":"2021-02-27","cited_by_count":2,"area":null},{"id":"2106.02745","title":"Neural Auto-Curricula","created":"2021-06-04","cited_by_count":2,"area":null},{"id":"2106.14668","title":"Evolutionary Dynamics and $\\Phi$-Regret Minimization in Games","created":"2021-06-28","cited_by_count":2,"area":null},{"id":"2201.04480","title":"Learning to Identify Top Elo Ratings: A Dueling Bandits Approach","created":"2022-01-12","cited_by_count":2,"area":null},{"id":"2209.10958","title":"Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments","created":"2022-09-22","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":"2402.19420","title":"Understanding Iterative Combinatorial Auction Designs via Multi-Agent Reinforcement Learning","created":"2024-02-29","cited_by_count":2,"area":null},{"id":"2405.18123","title":"PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2501.17559","title":"GraphChase: A Platform and Benchmark for Urban Network Security Games","created":"2025-01-29","cited_by_count":2,"area":null},{"id":"2602.13214","title":"BotzoneBench: Scalable LLM Evaluation via Graded AI Anchors","created":"2026-01-22","cited_by_count":2,"area":null},{"id":"2604.25796","title":"StratFormer: Adaptive Opponent Modeling and Exploitation in Imperfect-Information Games","created":"2026-04-28","cited_by_count":2,"area":null},{"id":"2605.14277","title":"Parallelizing Counterfactual Regret Minimization","created":"2026-05-14","cited_by_count":2,"area":null},{"id":"2609.31473","title":"Game Arena: Strategic LLM Evaluation in Competitive Environments","created":"2026-09-25","cited_by_count":2,"area":null},{"id":"2105.12328","title":"D2CFR: Minimize Counterfactual Regret with Deep Dueling Neural Network","created":"2021-05-26","cited_by_count":1,"area":null},{"id":"2307.09905","title":"PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games","created":"2023-07-19","cited_by_count":1,"area":null},{"id":"2311.01609","title":"Responsible Emergent Multi-Agent Behavior","created":"2023-11-02","cited_by_count":1,"area":null},{"id":"2404.11144","title":"Self-adaptive PSRO: Towards an Automatic Population-based Game Solver","created":"2024-04-17","cited_by_count":1,"area":null},{"id":"2405.11746","title":"Configurable Mirror Descent: Towards a Unification of Decision Making","created":"2024-05-20","cited_by_count":1,"area":null},{"id":"2405.14346","title":"Mixture of Public and Private Distributions in Imperfect Information Games","created":"2024-05-23","cited_by_count":1,"area":null},{"id":"2501.16600","title":"On the Power of Perturbation under Sampling in Solving Extensive-Form Games","created":"2025-01-28","cited_by_count":1,"area":null},{"id":"2503.12770","title":"Faster Game Solving via Asymmetry of Step Sizes","created":"2025-03-17","cited_by_count":1,"area":null},{"id":"2505.19837","title":"Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications","created":"2025-05-26","cited_by_count":1,"area":null},{"id":"2603.00374","title":"Conservative Equilibrium Discovery in Offline Game-Theoretic Multiagent Reinforcement Learning","created":"2026-02-27","cited_by_count":1,"area":null},{"id":"2606.29457","title":"How Much Due Diligence Before You Bid? Learning in Intractable Takeover Auctions","created":"2026-06-28","cited_by_count":1,"area":null},{"id":"2103.11517","title":"Dual Monte Carlo Tree Search","created":"2021-03-21","cited_by_count":0,"area":null},{"id":"2104.10845","title":"Optimize Neural Fictitious Self-Play in Regret Minimization Thinking","created":"2021-04-22","cited_by_count":0,"area":null}],"next_cursor":"100"}