Experts in Artificial Intelligence (AI) development predict that advances in the development of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted behaviors of intelligent agents, and at the same time specifying what we want such systems to do. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop our moral preferences simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic cognitive approach proposed by Dreyfus, whose phenomenological philosophy defends that the human experience of being-in-the-world cannot be represented by the symbolic or connectionist cognitive methods. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI.
The Animal-AI Environment: A Virtual Laboratory For Comparative Cognition and Artificial Intelligence Research
University of Cambridge（剑桥大学）；Universitat Politècnica de València（瓦伦西亚理工大学）；University of Hull（赫尔大学）；University of Exeter（埃克塞特大学）；Imperial College London（伦敦帝国学院）
Agent cognition through micro-simulations: Adaptive and tunable intelligence with NetLogo LevelSpace
Center for Connected Learning and Computer-Based Modeling（互联学习与计算机建模中心）；Northwestern Institute of Complex Systems（西北大学复杂系统研究所）；Northwestern University（西北大学）
Remapping and navigation of an embedding space via error minimization: a fundamental organizational principle of cognition in natural and artificial systems
Allen Discovery Center at Tufts University（塔夫茨大学阿伦发现中心）；Wyss Institute for Biologically Inspired Engineering at Harvard University（哈佛大学生物启发工程研究所）
The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition
Imperial College London（帝国理工学院）；Leverhulme Centre for the Future of Intelligence（利弗休姆未来智能中心）；Universitat Politècnica de València（瓦伦西亚理工大学）；University of Cambridge（剑桥大学）
Emotional intelligence in large language models is fragmented across perception, cognition, and interaction
X-LANCE Lab（X-LANCE实验室）；School of Computer Science, Shanghai Jiao Tong University（上海交通大学计算机科学学院）；MoE Key Lab of Artificial Intelligence（人工智能MOE重点实验室）；Jiangsu Key Lab of Language Computing（江苏省语言计算重点实验室）；Beijing Key Laboratory of Applied Experimental Psychology（北京应用实验心理学重点实验室）；National Demonstration Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal University（北京师范大学实验心理学教育国家级示范中心，心理学学院）
Artificial Intelligence : from Research to Application ; the Upper-Rhine Artificial Intelligence Symposium (UR-AI 2019)
TriRhenaTech联盟大学及其合作伙伴在2019年3月13日在奥芬堡举行的三国会议“人工智能：从研究到应用”上展示了他们在人工智能领域的能力以及与行业的跨境合作。TriRhenaTech联盟是上莱茵河三国大都市区的大学网络，包括位于富特旺根、凯泽斯滕、卡尔斯鲁厄和奥芬堡的德国应用科学大学，巴登-符腾堡州合作州立大学Loerrach，法国大学网络阿尔萨斯理工大学，瑞士国立大学（由14所工程、建筑和管理领域的“高等院校”组成）和瑞士西北应用科学与艺术大学（University of Applied Sciences and Arts Northwestern Switzerland）。该联盟的共同目标是加强知识、研究和技术的转移，以及学生的跨境流动。
Complex Systems Lab, Universitat Pompeu Fabra（复杂系统实验室，庞培法布拉大学）；Institució Catalana de la Recerca i Estudis Avançats (ICREA)（加泰罗尼亚高级研究与教育机构）；Institut de Biologia Evolutiva, CSIC-UPF（生物进化研究所，CSIC-UPF）；Santa Fe Institute（圣菲研究所）；School of Computing, Australian National University（澳大利亚国立大学计算机学院）；ISEM, Université de Montpellier, CNRS, IRD（蒙彼利埃大学ISEM，CNRS，IRD）；Allen Discovery Center, Tufts University（塔夫茨大学艾伦发现中心）；Wyss Institute for Biologically Inspired Engineering, Harvard University（哈佛大学生物启发工程研究所）
