A new cognitive model: Cloud model

Authors:
Deyi Li;Changyu Liu;Wenyan Gan
Affiliations:
School of Software, Tsinghua University, Beijing 100084, People's Republic of China and Institute of Electronic System Engineering, Beijing 100039, People's Republic of China;National Defense University of PLA, Beijing 100091, People's Republic of China;School of Software, Tsinghua University, Beijing 100084, People's Republic of China
Venue:
International Journal of Intelligent Systems
Year:
2009

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Abstract

Randomness and fuzziness are the two most important uncertainties inherent in human cognition, which have attracted great attention in artificial intelligence research. In this paper, regarding linguistic terms or concepts as the basic units of human cognition, we propose a new cognitive model—cloud model, which can synthetically describe the randomness and fuzziness of concepts and implement the uncertain transformation between a qualitative concept and its quantitative instantiations. Furthermore, by analyzing in detail the statistical properties of normal cloud model, that is, an important kind of cloud models based on normal distribution and Gauss membership function, we show that normal cloud model can not only be viewed as a generalized normal distribution with weak constraints but also avoid the flaw of fuzzy sets to quantify the membership degree of an element as an accurate value between 0 and 1 and, therefore, may be more adaptive for the uncertainty description of linguistic concepts. Finally, two demonstration examples about the fractal evolution of plants and network topologies based on cloud models are given to illustrate the promising applications of cloud models in some more complex knowledge representation tasks. © 2009 Wiley Periodicals, Inc.