DocumentCode :
1625989
Title :
A hypothalamic and piagetian fuzzy inference system: HtPFIS
Author :
Cheu, Eng-Yeow ; Ng, See-Kiong ; Quek, Chai
Author_Institution :
Centre for Comput. Intell., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2009
Firstpage :
1
Lastpage :
6
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.
Keywords :
fuzzy neural nets; inference mechanisms; knowledge based systems; action-based cognitive development; anterior hypothalamus; concise fuzzy rules knowledge base; fuzzy rules; hypothalamic fuzzy inference system; learning algorithm; model externalization; neuro-fuzzy system; neuronal circuitries; piagetian fuzzy inference system; Biological system modeling; Circuits; Computer networks; Fuzzy neural networks; Fuzzy systems; Humans; Inference algorithms; Neural networks; Space technology; Temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
ISSN :
1098-7584
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2009.5277213
Filename :
5277213
Link To Document :
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