A Whole Brain Probabilistic Generative Model: Toward Realizing Cognitive Architectures for Developmental Robots
Ritsumeikan University（立命馆大学）；The University of Tokyo（东京大学）；The Whole Brain Architecture Initiative（全脑架构倡议）；Osaka University（大阪大学）；Okinawa Institute of Science and Technology Graduate University（冲绳科学技术大学院大学）；Tamagawa University（玉川大学）；The University of Electro-Communications（电气通信大学）
Building a humanlike integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthermore, a computational model that enables an artificial system to achieve cognitive development will be an excellent reference for brain and cognitive science. This paper describes an approach to develop a cognitive architecture by integrating elemental cognitive modules to enable the training of the modules as a whole. This approach is based on two ideas: (1) brain-inspired AI, learning human brain architecture to build human-level intelligence, and (2) a probabilistic generative model(PGM)-based cognitive system to develop a cognitive system for developmental robots by integrating PGMs. The development framework is called a whole brain PGM (WB-PGM), which differs fundamentally from existing cognitive architectures in that it can learn continuously through a system based on sensory-motor information. In this study, we describe the rationale of WB-PGM, the current status of PGM-based elemental cognitive modules, their relationship with the human brain, the approach to the integration of the cognitive modules, and future challenges. Our findings can serve as a reference for brain studies. As PGMs describe explicit informational relationships between variables, this description provides interpretable guidance from computational sciences to brain science. By providing such information, researchers in neuroscience can provide feedback to researchers in AI and robotics on what the current models lack with reference to the brain. Further, it can facilitate collaboration among researchers in neuro-cognitive sciences as well as AI and robotics.
World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges
Ritsumeikan University（立命馆大学）；Keio University（庆应义塾大学）；The University of Tokyo（东京大学）；Università Milano-Bicocca（米兰比可卡大学）；University of Essex（埃塞克斯大学）；Donders Institute for Brain, Cognition and Behaviour（唐德斯脑、认知与行为研究所）；Cajal International Neuroscience Center, Spanish National Research Council（西班牙国家研究委员会卡哈尔国际神经科学中心）；Bogazici University（博阿齐奇大学）；Queen Mary University of London（伦敦玛丽女王大学）；The University of Electro-Communications（电气通信大学）；National Autonomous University of Mexico（墨西哥国立自治大学）；Universidad Autónoma del Estado de Morelos（莫雷洛斯州自治大学）；Institute of Cognitive Sciences and Technologies, National Research Council of Italy（意大利国家研究委员会认知科学与技术研究所）
Continual Developmental Neurosimulation Using Embodied Computational Agents
Orthogonal Research and Education Laboratory（正交研究与教育实验室）；OpenWorm Foundation（OpenWorm基金会）；Technical University of Munich（慕尼黑工业大学）；Manipal Institute of Technology（马尼帕尔理工学院）；Plot Twisters
Long-Term Simulation Exposes Cognitive-Developmental Risks in AI Companions
Shanghai Institute of Artificial Intelligence for Education, East China Normal University（华东师范大学上海人工智能教育研究院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；School of Computer Science and Technology, East China Normal University（华东师范大学计算机科学与技术学院）
A3RNN: Bi-directional Fusion of Bottom-up and Top-down Process for Developmental Visual Attention in Robots
Department of Intermedia Art and Science, Waseda University（媒体艺术与科学系，早稻田大学）；Research Development Group, Hitachi, Ltd.（日立株式会社研发发展组）；National Institute of Advanced Industrial Science and Technology (AIST)（国家先进工业科学与技术研究院）
Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI
University of Science and Technology of China（中国科学技术大学）；Nanjing University（南京大学）；University of New South Wales（新南威尔士大学）；Shanghai Jiao Tong University（上海交通大学）；Peking University（北京大学）；Harbin Institute of Technology（哈尔滨工业大学）；Tongji University（同济大学）；The University of Sydney, Oxford（悉尼大学，牛津）；Renmin University of China（中国人民大学）；Swiss Federal Institute of Technology Lausanne（苏黎世联邦理工学院）；Shanghai Institute of Ceramics, Chinese Academy of Sciences（中国科学院上海硅酸盐研究所）；Shanghai AI Laboratory（上海人工智能实验室）；Shanghai AI Laboratory & The Chinese University of Hong Kong（上海人工智能实验室 & 香港中文大学）
Symbol Emergence in Cognitive Developmental Systems: a Survey
Ritsumeikan University（立命馆大学）；Bogazici University（海峡大学）；Czech Technical University in Prague（布拉格捷克理工大学）；Queen Mary University of London（伦敦玛丽女王大学）；The University of Electro-communications（电气通信大学）；Council for Scientific and Industrial Research（科学与工业研究理事会）；University of the Witwatersrand（金山大学）；Chiba University（千叶大学）；Okayama Prefectural University（冈山县立大学）；Ozyegin University（厄兹耶因大学）；Universität Innsbruck（因斯布鲁克大学）
From Modelling to Understanding Children's Behaviour in the Context of Robotics and Social Artificial Intelligence
Donders Institute for Brain, Cognition, and Behaviour（唐德斯大脑、认知与行为研究所）；Radboud University（拉德堡德大学）；Joint Research Centre, European Commission（欧盟委员会联合研究中心）；Ghent University（根特大学）；imec（微电子研究中心）；Instituto Superio Técnico（高等技术学院）；University of Lisbon（里斯本大学）
Continual Learning of Multiple Cognitive Functions with Brain-inspired Temporal Development Mechanism
State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences（中国科学院脑认知与类脑智能技术国家重点实验室）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Center for Long-term Artificial Intelligence（长期人工智能中心）
Human-AI Coevolution Dynamics: A Formal Theory of Social Intelligence Emergence Through Long-Term Interaction
School of Information and Electronics, Beijing Institute of Technology（信息与电子学院，北京理工大学）；Institute of Scientific and Technical Research on Archives, Beijing（档案科学与技术研究所，北京）；China Electronics Engineering Design Institute Co., Ltd.（中国电子工程设计院有限公司）
Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for Cognitive and Psychiatric Applications
Interdisciplinary Program in Artificial Intelligence（人工智能跨学科项目）；Seoul National University（首尔国立大学）；Department of Psychology（心理学系）；University of Texas at Austin（德克萨斯大学奥斯汀分校）；Brookhaven National Laboratory（布鲁赫斯国家实验室）；Computational Science Initiative（计算科学倡议）；Department of Brain and Cognitive Sciences（脑科学与认知科学系）
Cognitive Science-Inspired Evaluation of Core Capabilities for Object Understanding in AI
University of Cambridge（剑桥大学）；Universitat Politècnica de València（瓦伦西亚理工大学）；Sigmund Freud University（西格蒙德·弗洛伊德大学）；University of Primorska（普里莫尔斯卡大学）；Helmholtz Institute for Human-Centered AI（亥姆霍兹以人为本人工智能研究所）
A Heuristic Search Algorithm Using the Stability of Learning Algorithms in Certain Scenarios as the Fitness Function: An Artificial General Intelligence Engineering Approach
Huawei 2012 Lab Central Software Institute（华为2012实验室中央软件院）
Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds
Catholic University of Sacred Heart（圣心天主教大学）；Istituto Auxologico Italiano IRCCS（意大利奥索洛吉科研究所）；University of Milano - Bicocca（米兰比可卡大学）；Virtual Reality Medical Center（虚拟现实医疗中心）；Interactive Media Institute（交互媒体研究所）
Parsing altered brain connectivity in neurodevelopmental disorders by integrating graph-based normative modeling and deep generative networks
University of Pennsylvania（宾夕法尼亚大学）；Perelman School of Medicine, University of Pennsylvania（宾夕法尼亚大学佩雷尔曼医学院）；Drexel University（德雷塞尔大学）；Children’s Hospital of Philadelphia（费城儿童医院）
