{"total":18,"rows":[{"id":"2209.03859","title":"A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning","created":"2022-09-08","cited_by_count":14,"area":null},{"id":"2102.06042","title":"Modeling the Interaction between Agents in Cooperative Multi-Agent Reinforcement Learning","created":"2021-02-10","cited_by_count":7,"area":null},{"id":"2305.10091","title":"Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges","created":"2023-05-17","cited_by_count":5,"area":null},{"id":"2208.08056","title":"Sampling Through the Lens of Sequential Decision Making","created":"2022-08-17","cited_by_count":4,"area":null},{"id":"2303.10665","title":"Major-Minor Mean Field Multi-Agent Reinforcement Learning","created":"2023-03-19","cited_by_count":4,"area":null},{"id":"2102.02304","title":"Improved Cooperation by Exploiting a Common Signal","created":"2021-02-03","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":"2108.07970","title":"Scalable regret for learning to control network-coupled subsystems with unknown dynamics","created":"2021-08-18","cited_by_count":2,"area":null},{"id":"2408.15173","title":"Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning","created":"2024-08-27","cited_by_count":2,"area":null},{"id":"2310.16326","title":"Reinforcement Learning for SBM Graphon Games with Re-Sampling","created":"2023-10-25","cited_by_count":1,"area":null},{"id":"2507.10142","title":"Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review","created":"2025-07-14","cited_by_count":1,"area":null},{"id":"2212.13379","title":"Learning Individual Policies in Large Multi-agent Systems through Local Variance Minimization","created":"2022-12-27","cited_by_count":0,"area":null},{"id":"2306.02766","title":"Networked Communication for Decentralised Agents in Mean-Field Games","created":"2023-06-05","cited_by_count":0,"area":null},{"id":"2308.03995","title":"Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks","created":"2023-08-08","cited_by_count":0,"area":null},{"id":"2408.11607","title":"Networked Communication for Mean-Field Games with Function Approximation and Empirical Mean-Field Estimation","created":"2024-08-21","cited_by_count":0,"area":null},{"id":"2505.06706","title":"Bi-level Mean Field: Dynamic Grouping for Large-Scale MARL","created":"2025-05-10","cited_by_count":0,"area":null},{"id":"2509.15103","title":"Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2610.09244","title":"Beyond Nominal Equilibria: Risk-Averse Multi-Population Mean-Field Games","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}