Bar Ilan University（巴伊兰大学）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；The University of Edinburgh（爱丁堡大学）；The University of Birmingham（伯明翰大学）；Sony AI（索尼人工智能）
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Elliot Fosong, William Macke, Mohan Sridharan, Peter Stone, Stefano V. Albrecht
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European Conference on Multi-Agent Systems (EUMAS), 2022
Ad hoc teamwork is the research problem of designing agents that can collaborate with new teammates without prior coordination. This survey makes a two-fold contribution: First, it provides a structured description of the different facets of the ad hoc teamwork problem. Second, it discusses the progress that has been made in the field so far, and identifies the immediate and long-term open problems that need to be addressed in ad hoc teamwork.
Making Friends in the Dark: Ad Hoc Teamwork Under Partial Observability
INESC-ID（INESC-ID（高等工程系统与计算机研究所））；Instituto Superior Técnico, University of Lisbon（里斯本大学高等技术学院）；Pontifícia Universidade Católica do Rio de Janeiro（里约热内卢天主教大学）
ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork
Department of Computer Science（计算机科学系）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；College of Computing and Data Science（计算与数据科学学院）；Nanyang Technological University（南洋理工大学）
Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
INFORMED-AI Hub University of Bristol, UK（INFORMED-AI Hub 英国布里斯托大学）；Centre for AI Fundamentals University of Manchester, UK（人工智能基础研究中心 英国曼彻斯特大学）；School of Engineering Mathematics and Technology University of Bristol, UK（工程数学与技术学院 英国布里斯托大学）
Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
Beijing University of Posts and Telecommunications（北京邮电大学）；Beijing Institute of Technology（北京理工大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Tsinghua University（清华大学）
