{"total":11,"rows":[{"id":"2410.23208","title":"Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks","created":"2024-10-30","cited_by_count":45,"area":null},{"id":"2506.14990","title":"MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning","created":"2025-06-17","cited_by_count":11,"area":null},{"id":"2505.23686","title":"ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork","created":"2025-05-29","cited_by_count":6,"area":null},{"id":"2504.15457","title":"Improving Human-AI Coordination through Online Adversarial Training and Generative Models","created":"2025-04-21","cited_by_count":3,"area":null},{"id":"2603.06009","title":"Preventing Learning Stagnation in PPO by Scaling to 1 Million Parallel Environments","created":"2026-03-06","cited_by_count":3,"area":null},{"id":"2508.12845","title":"CAMAR: Continuous Actions Multi-Agent Routing","created":"2025-08-18","cited_by_count":2,"area":null},{"id":"2606.08729","title":"IR-SIM: A Lightweight Declarative Simulator for Navigation Learning and Benchmarking","created":"2026-06-07","cited_by_count":2,"area":null},{"id":"2503.07275","title":"Automatic Curriculum Design for Zero-Shot Human-AI Coordination","created":"2025-03-10","cited_by_count":1,"area":null},{"id":"2602.01665","title":"TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2605.09212","title":"Rethinking Ratio-Based Trust Regions for Policy Optimization in Multi-Agent Reinforcement Learning","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2610.15328","title":"Anchor-and-Harvest Curriculum: A Fully Unmasked Non-LLM Curriculum for Craftax","created":"2026-10-11","cited_by_count":0,"area":null}],"next_cursor":null}