主题报告：认知信息学和神经信息学前沿
Latest Advances in Cognitive Informatics and Neuroinformatics
报告人：Yingxu Wang[University of Calgary, Canada]
报告时间：05月 20日（周二）14: 00～16: 00
报告地点：计算机学院大楼1001室
邀 请 人：骆祥峰 研究员

内容摘要：Cognitive informatics (CI) is a transdisciplinary field of sciences that studies the internal information processing mechanisms and processes of the brain, the underlying abstract intelligence (αI) theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems [Wang, 2002]. A key notion in CI is that the brain and natural intelligence may only be explained by a hierarchical and reductive theory that maps the brain across the embodied levels of neurology, physiology, cognition, and logic (mathematics). This talk presents formal models of the brain from the facets of CI, αI, brain Informatics, neuroinformatics, and cognitive science. A logical model of the brain is introduced that maps the cognitive functions of the brain onto its neural and physiological structures. This work leads to a coherent αI theory based on both denotational mathematical models and cognitive science observations, which rigorously explains the underpinning principles and mechanisms of the brain. On the basis of αI and the logical models of the brain, a comprehensive set of cognitive behaviors as identified in the Layered Reference Model of the Brain (LRMB) [Wang et al., 2006], such as perception, inference, and learning, can be rigorously explained and simulated. Investigations into the neurophysiological foundations of neural networks in neuroinformatics [Wang, 2014] have led to a set of rigorous mathematical models of neurons and neural networks in the brain using contemporary denotational mathematics [Wang, 2008, 2012]. A theory of neuroinformatics is recently developed for explaining the roles of neurons in internal information representation, transmission, and manipulation [Wang & Fariello, 2012]. The formal neural models reveal the differences of structures and functions of the association, sensory and motor neurons. The pulse frequency modulation (PFM) theory of neural networks is established for rigorously analyzing the neurosignal systems in complex neural networks. It is found that neural networks can be formally modeled and manipulated by the neural circuit theory[Wang, 2013]. Based on it, the basic structures of neural networks can be rigorously analyzed. Complex neural clusters for memory and internal knowledge representation can be deduced by compositions of the formal neuroinformatics models. The αI theory, neuroinformatics models, and denotational mathematics enable the development of cognitive computers that perceive, think, and learn. The functional and theoretical difference between cognitive computers and classic computers are that the latter are data processors based on Boolean algebra and its logical counterparts; while the former are knowledge processors based on contemporary denotational mathematics. A wide range of applications of cognitive computers have been developing in ICIC (http://www.ucalgary.ca/icic/) such as, inter alia, cognitive robots, cognitive learning engines, cognitive Internet, cognitive search engines, and cognitive systems.

Brief Biography: Yingxu Wang is professor of cognitive informatics and denotational mathematics, President of International Institute of Cognitive Informatics and Cognitive Computing (ICIC, http://www.ucalgary.ca/icic/) at the University of Calgary. He is a Fellow of ICIC, a Fellow of WIF (UK), a P.Eng of Canada, and a Senior Member of IEEE and ACM. He received a PhD in computer science from the Nottingham Trent University, UK. He was visiting professors on sabbatical leaves at Oxford University (1995), Stanford University (2008), University of California, Berkeley (2008), and MIT (2012), respectively. He is the founder and steering committee chair of the annual IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chief of International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), founding Editor-in-Chief of International Journal of Software Science and Computational Intelligence (IJSSCI), Associate Editor of IEEE Trans. on SMC (Systems), and Editor-in-Chief of Journal of Advanced Mathematics and Applications (JAMA). Dr. Wang is the initiator of a few cutting-edge research fields such as cognitive informatics, denotational mathematics (concept algebra, process algebra, system algebra, semantic algebra, and inference algebra), abstract intelligence (αI), cognitive computing, cognitive knowledge base, fuzzy mathematics (fuzzy arithmetic , fuzzy functions, fuzzy probability theory, fuzzy statistics, and fuzzy inference algebra), and basic studies in neuroinformatics, software science, cognitive linguistics, and computational intelligence. He has published over 160 peer reviewed journal papers, 230+ peer reviewed conference papers, and 25 books in denotational mathematics, cognitive informatics, software science, and computational intelligence. He is the recipient of dozens international awards on academic leadership, outstanding contributions, best papers, and teaching in the last three decades.