On the cognitive process of human problem solving

  • Authors:

  • Yingxu Wang;Vincent Chiew

  • Affiliations:

  • International Center for Cognitive Informatics (ICfCI) and Theoretical and Empirical Software Engineering Research Centre, Department of Electrical and Computer Engineering, Schulich School of Eng ...;International Center for Cognitive Informatics (ICfCI) and Theoretical and Empirical Software Engineering Research Centre, Department of Electrical and Computer Engineering, Schulich School of Eng ...

  • Venue:
  • Cognitive Systems Research
  • Year:
  • 2010

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Abstract

One of the fundamental human cognitive processes is problem solving. As a higher-layer cognitive process, problem solving interacts with many other cognitive processes such as abstraction, searching, learning, decision making, inference, analysis, and synthesis on the basis of internal knowledge representation by the object-attribute-relation (OAR) model. Problem solving is a cognitive process of the brain that searches a solution for a given problem or finds a path to reach a given goal. When a problem object is identified, problem solving can be perceived as a search process in the memory space for finding a relationship between a set of solution goals and a set of alternative paths. This paper presents both a cognitive model and a mathematical model of the problem solving process. The cognitive structures of the brain and the mechanisms of internal knowledge representation behind the cognitive process of problem solving are explained. The cognitive process is formally described using real-time process algebra (RTPA) and concept algebra. This work is a part of the cognitive computing project that designed to reveal and simulate the fundamental mechanisms and processes of the brain according to Wang's layered reference model of the brain (LRMB), which is expected to lead to the development of future generation methodologies for cognitive computing and novel cognitive computers that are capable of think, learn, and perceive.