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The Research of Attribute Granular Computing Model in Cognitive and Decision-Making

Abstract : The cognitive activities of human beings are complicate and diversified. So far, there hasn’t been a universal cognitive model. Each cognitive model generally only represents cognitive features in one or some aspects. Therefore, this paper aims to, based on the granular computing theory and principles, and with attributes and change laws as the main objects of the cognitive course, proposes a cognitive model which not only can describe the thing through attributes to represent the change law, but also can simulate the cognitive decision-making course with respect to the attribute change of the thing. Attribute granular computing, based on qualitative mapping, can simulate the cognitive functions of human brain, such as granulation, organization and causation. Petri net has asynchronous, concurrent and uncertainty characteristics, which is similar to the characteristics of some cognitive activities in human thinking process. Petri net is extended based on the basic concept and logic calculation rules of attribute granular computing in this paper. Some basic elements of a cognitive system, such as knowledge representation, reasoning, learning and memory mode are initially showed in the extended Petri net. The results show that this method can reflect the cognitive process of uncertainty identification and decision-making in a certain extent.
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Ruqi Zhou, Yuepeng Zhou. The Research of Attribute Granular Computing Model in Cognitive and Decision-Making. 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.93-103, ⟨10.1007/978-3-319-68121-4_10⟩. ⟨hal-01820916⟩

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