AUV fuzzy neural BDI |
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| Authors: | Liu Hai-bo Gu Guo-chang Shen Jing Fu Yan |
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| Institution: | (1) School of Computer Science and Technology, Harbin Engineering University, 150001 Harbin, China |
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| Abstract: | The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers; input ( beliefs and desires) , fuzzification, commitment , fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game) , and the simulation result is satisfactory. |
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| Keywords: | autonomous underwater vehicle fuzzy neural network belief-desire-intention pursuit-evasion game |
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