Perspectives on Cognitive Computing and Applications

Cognitive Computing: Theories And Applications

The latest advances in cognitive informatics, abstract intelligence, and denotational mathematics have led to a systematic solution for the future generation of intelligent computers known as cognitive computers (cCs) that think, perceive, learn, and reason (Wang, 2006, 2009a, 2009b). A cC is an intelligent computer for knowledge processing as that of a conventional von Neumann computer for data processing. cCs are designed to embody machinable intelligence such as computational inferences, causal analyses, knowledge manipulation, learning, and problem solving.

The term computing in a narrow sense is an application of computers to solve a given problem by imperative instructions; while in a broad sense, it is a process to implement the instructive intelligence by a system that transfers a set of given information or instructions into expected intelligent behaviors.

The essences of computing are both its data objects and their predefined computational operations. From these facets, different computing paradigms may be comparatively analyzed as follows:

• (a)

  Conventional computing

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    Data objects: abstract bits and structured data

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    Operations: logic, arithmetic, and functions

• (b)

  Cognitive computing (CC)

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    Data objects: words, concepts, syntax, and semantics

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    Basic operations: syntactic analyses and semantic analyses

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    Advanced operations: concept formulation, knowledge representation, comprehension, learning, inferences, and causal analyses