Key papers

• Generalization In Mean Field Games By Learning Master Policies (2021)
  Sarah Perrin, Mathieu Laurière, Julien Pérolat, et al.
  7.81
• Opponent Learning Awareness And Modelling In Multi-objective Normal Form Games (2020)
  Roxana Rădulescu, Timothy Verstraeten, Yijie Zhang, et al.
  7.16
• Holistic Data Scheduler for LLM Pre-training via Multi-Objective Reinforcement Learning (2026)
  Chenhao Dang et al.
  6.43
• A Large Language Model-Driven Agent-Based Modeling Framework with Multi-Round Communication for Simulating Vaccine Opinion Dynamics (2026)
  Bo Zhang et al.
  5.89
• Operational Reframing and Approval-Framed Delegation in Multi-Agent LLM Safety (2026)
  Lifei Liu et al.
  5.01
• Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning (2026)
  Zetian Hu et al.
  5.01
• From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents (2026)
  Haipeng Ding et al.
  5.01
• SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis (2026)
  Songhan Wang et al.
  5.01
• A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling (2026)
  Shivendra G. Tewari et al.
  5.01
• Institutional Red-Teaming: Deployment Rules, Not Just Models, Causally Shape Multi-Agent AI Safety (2026)
  Yujiao Chen
  5.01
• Reinforcement Learning With Success Induced Task Prioritization (2022)
  Maria Nesterova, Alexey Skrynnik, Aleksandr Panov
  4.52
• Toward Evaluating Robustness Of Reinforcement Learning With Adversarial Policy (2023)
  Xiang Zheng, Xingjun Ma, Shengjie Wang, et al.
  4.52
• Simulation Based Reward Function Validation for Multi-Agent On Orbit Inspection (2026)
  Patrick Quinn et al.
  4.39
• Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory (2026)
  Jihao Liu et al.
  4.39
• Format-Controlled Multi-Scale JPEG Compression Response Analysis for Image-Level Forgery Screening (2026)
  Sujith K Mandala
  4.39
• A Multi-Analyst LLM Pipeline for Auditable Rule Discovery Across 68 Public Physiological Corpora (2026)
  Dovy Paukstys
  4.39
• When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems (2026)
  Haowen Xu et al.
  4.39
• Evaluating SageMath-Augmented LLM Agents for Computational and Experimental Mathematics (2026)
  Pavel Snopov et al.
  4.39
• Compass: Prostate Cancer Detection Needs Multi-View Context (2026)
  Paul F. R. Wilson et al.
  4.39
• MADB: A Large-Scale Music Aesthetics Dataset with Professional and Multi-Dimensional Annotations (2026)
  Sirui Zhang et al.
  4.39
• Comprehensive Evaluation of Large Language Model Responses: A Multi-Factor Scoring System (2026)
  Yiming Gai et al.
  4.39
• Flow-ERD: Agent-type Aware Flow Matching with Entropy-Regularized Distillation for Diverse Traffic Simulation (2026)
  Seulbin Hwang et al.
  4.39
• End-to-End LLM Flight Planning with RAG-based Memory and Multi-modal Coach Agent (2026)
  Amin Tabrizian et al.
  4.39
• Gimitest: A Comprehensive Tool for Testing Reinforcement Learning Policies (2026)
  Dennis Gross et al.
  4.39
• Behavior Leverage Imbalance in Multi-Teacher On-Policy Distillation (2026)
  Jiabin Shen et al.
  4.39
• Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors (2026)
  Oliver Makins et al.
  4.39
• Multi-Agent Robotic Control with Onboard Vision-Language Models (2026)
  Kajetan Rachwa{\l} et al.
  4.39
• Multi-Class vs. Multi-Label BERT for CVE-to-CWE Mapping: How Taxonomy Structure Shapes the Errors (2026)
  Ana Schwengber Kelm et al.
  4.39
• SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents (2026)
  Tianming Sha et al.
  4.39
• Agent Delivery Engineering Predictive Reliability Framework (2026)
  Dexing Liu (Shanghai Qijing Digital Technology Co. et al.
  4.39
• Safety-Contract Graph Multi-Agent Reinforcement Learning for Autonomous Network Security Response (2026)
  Jose Luis Lima de Jesus Silva
  4.33
• Temporally Consistent Graph Q-Networks for Intelligent Network Control (2026)
  Zacharias Veiksaar et al.
  4.33
• Contract-Based Compositional Shielding for Safe Multi-Agent Reinforcement Learning (2026)
  Omar Adalat et al.
  4.33
• Learning Coordinated Preference for Multi-Objective Multi-Agent Reinforcement Learning (2026)
  Pengxin Wang et al.
  4.33
• Pareto Q-Learning with Reward Machines (2026)
  Arnaud Lequen et al.
  4.33
• ASALT: Adaptive State Alignment for Lateral Transfer in Multi-agent Reinforcement Learning (2026)
  Anurag Akula et al.
  4.33
• Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models (2026)
  Thibaut Kulak
  4.33
• Bias-Controlled Primal-Dual Natural Actor-Critic: Optimal Rates for Constrained Multi-Objective Average-Reward RL (2026)
  Ankur Naskar et al.
  4.33
• GCT-MARL: Graph-Based Contrastive Transfer for Sample-Efficient Cooperative Multi-Agent Reinforcement Learning (2026)
  Animesh Animesh et al.
  4.33
• Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning (2026)
  Bang Giang Le et al.
  4.33
• Memory-Efficient Policy Libraries with Low-Rank Adaptation in Reinforcement Learning (2026)
  Samuel Valland Lyngset et al.
  4.33
• Semantic Consistency Policy Optimization for Reinforcement Learning of LLM Agents (2026)
  Peng Xu et al.
  4.33
• Fake News in Social Networks (2017)
  Christoph Aymanns and Jakob Foerster and Co-Pierre Georg and Matthias Weber
  4.13
• Empowering Economic Simulation For Massively Multiplayer Online Games Through Generative Agent-based Modeling (2025)
  Bihan Xu, Shiwei Zhao, Runze Wu, et al.
  3.81
• GTDE: Grouped Training With Decentralized Execution For Multi-agent Actor-critic (2024)
  Mengxian Li, Qi Wang, Yongjun Xu
  3.58
• TAPE: Leveraging Agent Topology For Cooperative Multi-agent Policy Gradient (2023)
  Xingzhou Lou, Junge Zhang, Timothy J. Norman, et al.
  3.58
• Convergence Of Decentralized Actor-critic Algorithm In General-sum Markov Games (2024)
  Chinmay Maheshwari, Manxi Wu, Shankar Sastry
  3.58
• Learning Cooperative Behaviours In Adversarial Multi-agent Systems (2023)
  Ni Wang, Gautham P. Das, Alan G. Millard
  3.58
• Tandem Reinforcement Learning with Verifiable Rewards (2026)
  Difan Jiao et al.
  3.45
• Discovering Multiagent Learning Algorithms with Large Language Models (2026)
  Zun Li et al.
  3.30
• CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving (2025)
  Xiaoji Zheng et al.
  3.10
• Collaborative Value Function Estimation Under Model Mismatch: A Federated Temporal Difference Analysis (2025)
  Ali Beikmohammadi, Sarit Khirirat, Peter Richtárik, et al.
  2.87
• General Agents Contain World Models (2025)
  Jonathan Richens, David Abel, Alexis Bellot, et al.
  2.87
• RollArt: Scaling Agentic RL Training via Disaggregated Infrastructure (2025)
  Wei Gao et al.
  2.68
• R2D-RL: A RoboCup 2D Soccer Environment for Multi-Agent Reinforcement Learning (2026)
  Haobin Qin et al.
  1.94
• CAPO: Counterfactual Credit Assignment In Sequential Cooperative Teams (2026)
  Shripad Deshmukh, Jayakumar Subramanian, Raghavendra Addanki, et al.
  1.94
• Learning To Share: Selective Memory For Efficient Parallel Agentic Systems (2026)
  Joseph Fioresi, Parth Parag Kulkarni, Ashmal Vayani, et al.
  1.94
• Hierarachical Multiagent Reinforcement Learning For Multi-group Tax Game (2026)
  Honglei Guo, Yuhan Zhao, Yexin Li
  1.94
• Design Experiments To Compare Multi-armed Bandit Algorithms (2026)
  Huiling Meng, Ningyuan Chen, Xuefeng Gao
  1.94
• Epistemic Context Learning: Building Trust The Right Way In Llm-based Multi-agent Systems (2026)
  Ruiwen Zhou, Maojia Song, Xiaobao Wu, et al.
  1.94