There is an increasing need to develop artificial intelligence systems that assist groups of humans working on coordinated tasks. These systems must recognize and understand the plans and relationships between actions for a team of humans working toward a common objective. This article reviews the literature on team plan recognition and surveys the most recent logic-based approaches for implementing it. First, we provide some background knowledge, including a general definition of plan recognition in a team setting and a discussion of implementation challenges. Next, we explain our reasoning for focusing on logic-based methods. Finally, we survey recent approaches from two primary classes of logic-based methods (plan library-based and domain theory-based). We aim to bring more attention to this sparse but vital topic and inspire new directions for implementing team plan recognition.
Multi-Agent Goal Recognition with Team- and Goal-Conditioned Reinforcement Learning and Factorized Branch-and-Bound
Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)（里约格兰德杜斯阿伦斯天主教大学）；Universidade do Vale do Rio dos Sinos (Unisinos)（里约斯inos大学）；University of Aberdeen（阿伯丁大学）
HSEmotion Team at ABAW-10 Competition: Facial Expression Recognition, Valence-Arousal Estimation, Action Unit Detection and Fine-Grained Violence Classification
Team RAS in 11th ABAW Competition: Multimodal Ambivalence Recognition Approach
St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS)（俄罗斯科学院圣彼得堡联邦研究中心）；HSE University（圣彼得堡高等经济学院）；ITMO University（圣彼得堡国立信息技术机械与光学大学）
Development and multi-center evaluation of domain-adapted speech recognition for human-AI teaming in real-world gastrointestinal endoscopy
Zhejiang University（浙江大学）；Shanghai Institute for Advanced Study, Zhejiang University（浙江大学上海高等研究院）；Shanghai Key Laboratory of MICCAI（上海市MICCAI重点实验室）；Digital Medical Research Center, School of Basic Medical Sciences, Fudan University（复旦大学基础医学院数字医学研究中心）；Endoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University（复旦大学附属中山医院内镜中心及内镜研究所）；Shanghai Collaborative Innovation Center of Endoscopy（上海市内镜协同创新中心）；Alliance Manchester Business School, The University of Manchester（曼彻斯特大学联盟曼彻斯特商学院）
Summary of the Unusual Activity Recognition Challenge for Developmental Disability Support
Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology（九州工学技术大学生命科学与系统工程研究生院）；Department of Biomedical Engineering, Ho Chi Minh City University of Technology（胡志明市技术大学生物医学工程系）
Trainee Action Recognition through Interaction Analysis in CCATT Mixed-Reality Training
Vanderbilt University（范德堡大学）；Air Force Research Laboratory（美国空军研究实验室）；US Army CCDC Soldier Center（美国陆军作战能力发展司令部士兵中心）；Institute for Software-Integrated Systems（软件集成系统研究所）；University of Cincinnati（辛辛那提大学）
