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
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.
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