Perspectives on Cognitive Computers and Knowledge Processors

Perspectives on Cognitive Computers and Knowledge Processors

Yingxu Wang, Gabriele Fariello, Marina L. Gavrilova, Witold Kinsner, Fumio Mizoguchi, Shushma Patel, Dilip Patel, Fernando L. Pelayo, Victor Raskin, Duane F. Shell, Shusaku Tsumoto
DOI: 10.4018/ijcini.2013070101
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Abstract

Cognitive Informatics (CI) is a contemporary multidisciplinary field spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, cognitive linguistics, and cognitive philosophy. CI aims to investigate the internal information processing mechanisms and processes of the brain, the underlying abstract intelligence theories and denotational mathematics, and their engineering applications in cognitive computing and computational intelligence. This paper reports a set of eleven position statements presented in the plenary panel of IEEE ICCI*CC’13 on Cognitive Computers and Knowledge Processors contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.
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1. Introduction

The theme of the 2013 IEEE International Conferences on Cognitive Informatics and Cognitive Computing (ICCI*CC’13) is on Cognitive Computers and Knowledge Processors. Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information science, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing (Wang, 2002a, 2003, 2006, 2007b, 2007c, 2007d, 2009a, 2009b, 2012c, 2012d, 2012f; Wang et al., 2011c, 2013; Wang and Kinsner, 2006; Wang and Wang, 2006; Wang and Berwick, 2012b; Wang et al., 2009b, 2009c, 2010, 2011b).

Fundamental theories developed in CI cover the Matter-Energy-Information-Intelligence (MEII) model (Wang, 2007a, 2007b), the Layered Reference Model of the Brain (LRMB) (Wang et al., 2006), the Object-Attribute-Relation (OAR) model of internal information representation in the brain (Wang, 2007c), the Cognitive Functional Model of the Brain (CFMB) (Wang & Wang, 2006), the Abstract Intelligence Model of the Brain (AIMB), Natural Intelligence (Wang, 2007b), Abstract Intelligence (Wang, 2009a, 2012c), Neuroinformatics (Wang, 2007b, 2013a, 2013b; Wang & Fariello, 2012a), Denotational Mathematics (Wang, 2002b, 2007a, 2008a, 2008b, 2008c, 2008d, 2009d, 2011a, 2011b, 2012a, 2012b, 2012e, 2012g, 2013c), Cognitive Linguistics (Wang & Berwick, 2012b; Wang, 2013d; Wang et al., 2012d), Formal Neural Signal and Circuit Theories (Wang & Fariello, 2012a), Cognitive Systems (Kinsner, 2011; Wang, 2010b, 2011c; Wang et al., 2011c, 2013). Recent studies on LRMB in cognitive informatics reveal an entire set of cognitive functions of the brain and their cognitive process models, which explain the functional mechanisms and cognitive processes of the natural intelligence with 48 cognitive processes at seven layers known as the sensation, action, memory, perception, meta-cognitive, inference, and advanced cognitive layers (Wang et al., 2006).

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