JRM Vol.17 No.6 pp. 689-696
doi: 10.20965/jrm.2005.p0689


Probabilistic Human Modeling Based on Personal Construct Theory

Yoichi Motomura, and Takeo Kanade

Digital Human Research Center, The National Institute of Advanced Industrial Science and Technology / CREST, JST

January 28, 2005
April 1, 2005
December 20, 2005
personal construct theory, cognitive human model, Bayesian network, evaluation grid, probabilistic modeling
We have initiated a project for constructing a mathematical model of human cognitive and psychological functions, executable on a computer. To this end, we propose probabilistic modeling based on the Personal Construct Theory, a basic theory used in cognitive/evaluative structure models for individuals. After extracting a skeleton structure using the Evaluation Grid, Bayesian network model is constructed though data learning. By executing a probabilistic reasoning algorithm on the constructed model, our proposal is applied to user-adaptable information systems, information recommendation, car navigation systems, etc.
Cite this article as:
Y. Motomura and T. Kanade, “Probabilistic Human Modeling Based on Personal Construct Theory,” J. Robot. Mechatron., Vol.17 No.6, pp. 689-696, 2005.
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