A hypothalamic and piagetian fuzzy inference system: HtPFIS

Authors:
Eng-Yeow Cheu;See-Kiong Ng;Chai Quek
Affiliations:
Centre for Computational Intelligence, Nanyang Technological University, Singapore;Institute for Infocomm Research, A*STAR, Singapore;Centre for Computational Intelligence, Nanyang Technological University, Singapore
Venue:
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Year:
2009

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Abstract

This paper presents a new approach to solving model externalization by taking into consideration the imprecise nature of decision makers' judgements on the different tacit models. Knowledge in the form of fuzzy rules are created using a neuro-fuzzy system called the Hypothalamic and Piagetian Fuzzy Inference System (HtPFIS). The structure of HtPFIS is inspired from the simplified neuronal circuitries of the preoptic area and anterior hypothalamus (PO/AH) which are involved in the thermoregulation of body temperature. HtPFIS employs a novel structure learning algorithm that is inspired from the Piaget's constructivist emphasis of action-based cognitive development in human. Results from the experiments show that HtPFIS is able to represent the formulated explicit model using a set of concise fuzzy rules knowledge base, and achieve better or comparable generalization than other models.