{"total":120,"rows":[{"id":"2401.01335","title":"Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models","created":"2024-01-02","cited_by_count":557,"area":"synth"},{"id":"2304.13653","title":"Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning","created":"2023-04-26","cited_by_count":133,"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":"2105.12196","title":"From Motor Control to Team Play in Simulated Humanoid Football","created":"2021-05-25","cited_by_count":87,"area":null},{"id":"2101.04882","title":"Asymmetric self-play for automatic goal discovery in robotic manipulation","created":"2021-01-13","cited_by_count":72,"area":null},{"id":"2105.00579","title":"BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning","created":"2021-05-02","cited_by_count":68,"area":null},{"id":"2107.07630","title":"Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi","created":"2021-07-15","cited_by_count":40,"area":null},{"id":"2305.03249","title":"PMP: Learning to Physically Interact with Environments using Part-wise Motion Priors","created":"2023-05-05","cited_by_count":38,"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":"2303.03376","title":"MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning","created":"2023-03-06","cited_by_count":31,"area":null},{"id":"2408.01072","title":"A Survey on Self-play Methods in Reinforcement Learning","created":"2024-08-02","cited_by_count":26,"area":"deeprl"},{"id":"2210.04688","title":"BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets","created":"2022-10-07","cited_by_count":25,"area":"offlinerl"},{"id":"2206.12301","title":"On the Limitations of Elo: Real-World Games, are Transitive, not Additive","created":"2022-06-21","cited_by_count":23,"area":null},{"id":"2506.01080","title":"The Coming Crisis of Multi-Agent Misalignment: AI Alignment Must Be a Dynamic and Social Process","created":"2025-06-01","cited_by_count":21,"area":"alignment"},{"id":"2509.10147","title":"Virtual Agent Economies","created":"2025-09-12","cited_by_count":21,"area":null},{"id":"2102.09812","title":"Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space","created":"2021-02-19","cited_by_count":20,"area":null},{"id":"2405.15815","title":"A social path to human-like artificial intelligence","created":"2024-05-22","cited_by_count":20,"area":null},{"id":"2202.03609","title":"PolicyCleanse: Backdoor Detection and Mitigation in Reinforcement Learning","created":"2022-02-08","cited_by_count":19,"area":null},{"id":"2107.01151","title":"Collaborative Visual Navigation","created":"2021-07-02","cited_by_count":18,"area":null},{"id":"2205.14205","title":"ALMA: Hierarchical Learning for Composite Multi-Agent Tasks","created":"2022-05-27","cited_by_count":18,"area":null},{"id":"2401.17173","title":"Zero-Shot Reinforcement Learning via Function Encoders","created":"2024-01-30","cited_by_count":18,"area":"deeprl"},{"id":"2109.06795","title":"ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation","created":"2021-09-14","cited_by_count":17,"area":null},{"id":"2405.02425","title":"Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning","created":"2024-05-03","cited_by_count":17,"area":"deeprl"},{"id":"2406.04274","title":"Self-Play with Adversarial Critic: Provable and Scalable Offline Alignment for Language Models","created":"2024-06-06","cited_by_count":16,"area":"alignment"},{"id":"2411.01775","title":"Eurekaverse: Environment Curriculum Generation via Large Language Models","created":"2024-11-04","cited_by_count":16,"area":null},{"id":"2202.10608","title":"It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation","created":"2022-02-22","cited_by_count":14,"area":null},{"id":"2406.10977","title":"Toward Optimal LLM Alignments Using Two-Player Games","created":"2024-06-16","cited_by_count":13,"area":"alignment"},{"id":"2407.08590","title":"A Review of Nine Physics Engines for Reinforcement Learning Research","created":"2024-07-11","cited_by_count":12,"area":"deeprl"},{"id":"2512.16856","title":"Distributional AGI Safety","created":"2025-12-18","cited_by_count":12,"area":null},{"id":"2210.13623","title":"Reinforcement Learning and Bandits for Speech and Language Processing: Tutorial, Review and Outlook","created":"2022-10-24","cited_by_count":10,"area":null},{"id":"2308.07795","title":"Learning to Identify Critical States for Reinforcement Learning from Videos","created":"2023-08-15","cited_by_count":9,"area":null},{"id":"2402.10236","title":"Discovering Sensorimotor Agency in Cellular Automata using Diversity Search","created":"2024-02-14","cited_by_count":9,"area":null},{"id":"2601.08198","title":"Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs","created":"2026-01-13","cited_by_count":9,"area":"synth"},{"id":"2103.11099","title":"Local Patch AutoAugment with Multi-Agent Collaboration","created":"2021-03-20","cited_by_count":8,"area":null},{"id":"2203.02119","title":"GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning","created":"2022-03-04","cited_by_count":8,"area":null},{"id":"2211.03352","title":"Curriculum-based Asymmetric Multi-task Reinforcement Learning","created":"2022-11-07","cited_by_count":8,"area":null},{"id":"2407.09502","title":"From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models","created":"2024-06-14","cited_by_count":8,"area":null},{"id":"2410.14152","title":"SRAP-Agent: Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent","created":"2024-10-18","cited_by_count":8,"area":"wm"},{"id":"2204.02558","title":"DouZero+: Improving DouDizhu AI by Opponent Modeling and Coach-guided Learning","created":"2022-04-06","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":"2402.03741","title":"SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems","created":"2024-02-06","cited_by_count":7,"area":null},{"id":"2601.03335","title":"Digital Red Queen: Adversarial Program Evolution in Core War with LLMs","created":"2026-01-06","cited_by_count":7,"area":null},{"id":"2605.15188","title":"FutureSim: Replaying World Events to Evaluate Adaptive Agents","created":"2026-05-14","cited_by_count":7,"area":null},{"id":"2305.11476","title":"Learning Diverse Risk Preferences in Population-based Self-play","created":"2023-05-19","cited_by_count":6,"area":null},{"id":"2310.03354","title":"Fictitious Cross-Play: Learning Global Nash Equilibrium in Mixed Cooperative-Competitive Games","created":"2023-10-05","cited_by_count":6,"area":null},{"id":"2110.04835","title":"Reinforcement Learning In Two Player Zero Sum Simultaneous Action Games","created":"2021-10-10","cited_by_count":4,"area":null},{"id":"2208.05083","title":"Reducing Exploitability with Population Based Training","created":"2022-08-10","cited_by_count":4,"area":null},{"id":"2210.10595","title":"DIAMBRA Arena: a New Reinforcement Learning Platform for Research and Experimentation","created":"2022-10-19","cited_by_count":4,"area":null},{"id":"2211.11043","title":"Revealing Robust Oil and Gas Company Macro-Strategies using Deep Multi-Agent Reinforcement Learning","created":"2022-11-20","cited_by_count":4,"area":null},{"id":"2506.05070","title":"RIVAL: Reinforcement Learning with Iterative and Adversarial Optimization for Machine Translation","created":"2025-06-05","cited_by_count":4,"area":"alignment"},{"id":"2106.08482","title":"Minimizing Communication while Maximizing Performance in Multi-Agent Reinforcement Learning","created":"2021-06-15","cited_by_count":3,"area":null},{"id":"2109.06523","title":"Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking","created":"2021-09-14","cited_by_count":3,"area":null},{"id":"2202.07068","title":"Motivating Physical Activity via Competitive Human-Robot Interaction","created":"2022-02-14","cited_by_count":3,"area":null},{"id":"2206.09046","title":"Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis","created":"2022-06-17","cited_by_count":3,"area":null},{"id":"2209.04696","title":"Cooperation and Competition: Flocking with Evolutionary Multi-Agent Reinforcement Learning","created":"2022-09-10","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":"2210.02769","title":"Artificial virtuous agents in a multiagent tragedy of the commons","created":"2022-10-06","cited_by_count":3,"area":null},{"id":"2305.02605","title":"Toward Evaluating Robustness of Reinforcement Learning with Adversarial Policy","created":"2023-05-04","cited_by_count":3,"area":null},{"id":"2305.03735","title":"Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula","created":"2023-05-04","cited_by_count":3,"area":null},{"id":"2306.04403","title":"Policy-Based Self-Competition for Planning Problems","created":"2023-06-07","cited_by_count":3,"area":null},{"id":"2306.08400","title":"Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning","created":"2023-06-14","cited_by_count":3,"area":null},{"id":"2310.16730","title":"MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning","created":"2023-10-25","cited_by_count":3,"area":"agents"},{"id":"2407.00662","title":"Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach","created":"2024-06-30","cited_by_count":3,"area":null},{"id":"2502.20065","title":"RouteRL: Multi-agent reinforcement learning framework for urban route choice with autonomous vehicles","created":"2025-02-27","cited_by_count":3,"area":"driving"},{"id":"2503.00372","title":"Nucleolus Credit Assignment for Effective Coalitions in Multi-agent Reinforcement Learning","created":"2025-03-01","cited_by_count":3,"area":null},{"id":"2511.22888","title":"Adversarial Training for Process Reward Models","created":"2025-11-28","cited_by_count":3,"area":"lr"},{"id":"2111.03431","title":"Learning to Cooperate with Unseen Agent via Meta-Reinforcement Learning","created":"2021-11-05","cited_by_count":2,"area":null},{"id":"2208.02932","title":"Human Decision Makings on Curriculum Reinforcement Learning with Difficulty Adjustment","created":"2022-08-04","cited_by_count":2,"area":null},{"id":"2210.16915","title":"Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games","created":"2022-10-30","cited_by_count":2,"area":"offlinerl"},{"id":"2310.04796","title":"Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning","created":"2023-10-07","cited_by_count":2,"area":null},{"id":"2311.17190","title":"Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play","created":"2023-11-28","cited_by_count":2,"area":null},{"id":"2405.18300","title":"CompetEvo: Towards Morphological Evolution from Competition","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2407.12505","title":"Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments","created":"2024-07-17","cited_by_count":2,"area":"deeprl"},{"id":"2609.07529","title":"CoER: Defending against Adaptive Indirect Prompt Injection via Adversarial Co-Evolution and Refinement","created":"2026-09-07","cited_by_count":2,"area":"agents"},{"id":"2109.00882","title":"MACRPO: Multi-Agent Cooperative Recurrent Policy Optimization","created":"2021-09-02","cited_by_count":1,"area":null},{"id":"2203.07562","title":"Safe adaptation in multiagent competition","created":"2022-03-14","cited_by_count":1,"area":null},{"id":"2209.02167","title":"Red Teaming with Mind Reading: White-Box Adversarial Policies Against RL Agents","created":"2022-09-05","cited_by_count":1,"area":"agents"},{"id":"2303.03068","title":"Reinforcement Learning Based Self-play and State Stacking Techniques for Noisy Air Combat Environment","created":"2023-03-06","cited_by_count":1,"area":null},{"id":"2312.02231","title":"Quality Diversity in the Amorphous Fortress (QD-AF): Evolving for Complexity in 0-Player Games","created":"2023-12-04","cited_by_count":1,"area":null},{"id":"2402.18617","title":"ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games","created":"2024-02-28","cited_by_count":1,"area":"offlinerl"},{"id":"2403.10487","title":"Stimulate the Potential of Robots via Competition","created":"2024-03-15","cited_by_count":1,"area":null},{"id":"2404.13150","title":"Transformer Based Planning in the Observation Space with Applications to Trick Taking Card Games","created":"2024-04-19","cited_by_count":1,"area":null},{"id":"2409.12997","title":"VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness","created":"2024-09-19","cited_by_count":1,"area":"driving"},{"id":"2409.19363","title":"Learning Strategy Representation for Imitation Learning in Multi-Agent Games","created":"2024-09-28","cited_by_count":1,"area":"offlinerl"},{"id":"2410.02128","title":"Breaking the mold: The challenge of large scale MARL specialization","created":"2024-10-03","cited_by_count":1,"area":null},{"id":"2503.15516","title":"In Pursuit of Predictive Models of Human Preferences Toward AI Teammates","created":"2025-01-31","cited_by_count":1,"area":null},{"id":"2510.01264","title":"HARL-A: An Extensible Benchmark Framework for Heterogeneous Multi-Agent Adversarial Reinforcement Learning in IsaacLab","created":"2025-09-26","cited_by_count":1,"area":null},{"id":"2511.02895","title":"A Criminology of Machines","created":"2025-11-04","cited_by_count":1,"area":null},{"id":"2511.13186","title":"DiffFP: Learning Behaviors from Scratch via Diffusion-based Fictitious Play","created":"2025-11-17","cited_by_count":1,"area":"deeprl"},{"id":"2603.11346","title":"Learning to Assist: Physics-Grounded Human-Human Control via Multi-Agent Reinforcement Learning","created":"2026-03-11","cited_by_count":1,"area":null},{"id":"2603.16279","title":"Agile Interception of a Flying Target using Competitive Reinforcement Learning","created":"2026-03-17","cited_by_count":1,"area":"deeprl"},{"id":"2605.22748","title":"Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2607.13028","title":"TerraZero: Procedural Driving Simulation for Zero-Demonstration Self-Play at Scale","created":"2026-07-14","cited_by_count":1,"area":"driving"},{"id":"2608.10299","title":"Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design","created":"2026-08-10","cited_by_count":1,"area":"agents"},{"id":"2106.03007","title":"Truthful Self-Play","created":"2021-06-06","cited_by_count":0,"area":null},{"id":"2110.01266","title":"Behaviour-conditioned policies for cooperative reinforcement learning tasks","created":"2021-10-04","cited_by_count":0,"area":null},{"id":"2203.02481","title":"AutoDIME: Automatic Design of Interesting Multi-Agent Environments","created":"2022-03-04","cited_by_count":0,"area":null},{"id":"2208.10327","title":"Incorporating Rivalry in Reinforcement Learning for a Competitive Game","created":"2022-08-22","cited_by_count":0,"area":null},{"id":"2301.08030","title":"Multi-Agent Interplay in a Competitive Survival Environment","created":"2023-01-19","cited_by_count":0,"area":null},{"id":"2304.00252","title":"Recover Triggered States: Protect Model Against Backdoor Attack in Reinforcement Learning","created":"2023-04-01","cited_by_count":0,"area":null}],"next_cursor":"100"}