Metacognition is the concept of reasoning about an agent's own internal processes and was originally introduced in the field of developmental psychology. In this position paper, we examine the concept of applying metacognition to artificial intelligence. We introduce a framework for understanding metacognitive artificial intelligence (AI) that we call TRAP: transparency, reasoning, adaptation, and perception. We discuss each of these aspects in-turn and explore how neurosymbolic AI (NSAI) can be leveraged to address challenges of metacognition.
NeuroSymbolic AI for Legal AI-TRISM: Trustworthy, Reliable, Interpretable, Safe Models
Department of Computer Science, AI Institute, University of South Carolina（南卡罗来纳大学计算机科学系，人工智能研究所）；Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County（马里兰大学巴尔的摩县分校计算机科学与电气工程系）；Department of Computer Science and Engineering, The Ohio State University（俄亥俄州立大学计算机科学与工程系）
Integrating Neurosymbolic AI in Advanced Air Mobility: A Comprehensive Survey
Department of Information Systems, University of Maryland, Baltimore County（信息系统系，马里兰大学巴尔的摩分校）；Department of Mechanical and Aerospace Engineering, The George Washington University（机械与航空航天工程系，乔治华盛顿大学）；Department of Mechanical Engineering, Baylor University（机械工程系，贝勒大学）
A homotopy-type-theoretic generalization of neurosymbolic inference
King Abdullah University of Science and Technology（阿卜杜拉国王科技大学）；KAUST Center of Excellence for Smart Health (KCSH)（KAUST智能健康卓越中心）；KAUST Center of Excellence for Generative AI（KAUST生成式人工智能卓越中心）
Sound and Complete Neurosymbolic Reasoning with LLM-Grounded Interpretations
University of Amsterdam（阿姆斯特丹大学）；University of Southern California（南加州大学）；Rensselaer Polytechnic Institute（拉特格斯理工学院）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）
Position: Artificial Intelligence Needs Meta Intelligence -- the Case for Metacognitive AI
University of Texas Rio Grande Valley, Edinburg, TX, USA（德克萨斯大学里奥格兰德谷分校）；Rochester Institute of Technology, Rochester, NY, USA（罗切斯特理工学院）；Syracuse University, Syracuse, NY, USA（锡拉库萨大学）
Publishing FAIR and Machine-actionable Reviews in Materials Science: The Case for Symbolic Knowledge in Neuro-symbolic Artificial Intelligence
TIB Leibniz Information Centre for Science and Technology（莱布尼茨科学技术信息中心）；L3S Research Center, Leibniz University Hannover（汉诺威莱布尼茨大学L3S研究中心）；Eindhoven University of Technology (TU/e)（埃因霍温理工大学）；University of Warwick（华威大学）；Leibniz Institute for Solid State and Materials Research (IFW)（莱布尼茨固体与材料研究所）
Autonomous Multi-Agent AI for High-Throughput Polymer Informatics: From Property Prediction to Generative Design Across Synthetic and Bio-Polymers
Institute of Biomedical Engineering University of Oxford（生物医学工程研究所牛津大学）；Department of Mechanical and Aerospace Engineering University of Missouri–Columbia（机械与航空航天工程系密苏里大学-哥伦比亚分校）；Center for Engineering, Modeling and Applied Social Sciences Federal University of ABC (UFABC)（工程、建模与应用社会科学中心巴西联邦大学ABC分校）
Robot Metacognition: Decision Making with Confidence for Tool Invention
Donders Institute, Radboud University（拉德堡德大学唐德斯研究所）；School of Engineering and Informatics, University of Sussex（萨塞克斯大学工程与信息学院）；Adaptive Systems, Department of Computer Science, Humboldt-Universität zu Berlin（柏林洪堡大学计算机科学系自适应系统）；Autonomous Systems Laboratory, Universidad Politécnica de Madrid（马德里理工大学自主系统实验室）；Neuro AI and Robotics, Cajal Neuroscience Center, Spanish National Research Council（西班牙国家研究委员会卡哈尔神经科学中心神经人工智能与机器人）
