DocumentCode :
2844392
Title :
A motivation based behavior in hybrid intelligent agents for intention reconsideration process in vessel berthing applications
Author :
Lokuge, Prasanna ; Alahakoon, Damminda
Author_Institution :
Sch. of Bus. Syst., Monash Univ., Clayton, Vic., Australia
fYear :
2004
fDate :
5-8 Dec. 2004
Firstpage :
124
Lastpage :
129
Abstract :
Strategic planning and dynamism in decision making are essential factors in a vessel berthing application in any container port to assure faster turnaround time and high productivity. BDI agents have been used in many applications with limited capabilities. We propose a new hybrid BDI architecture with learning capacities overcoming some limitations exists in the generic BDI agent model. A new "knowledge acquisition model" (KAM) module is proposed with a supervised neural network and adaptive neuro fuzzy inference system (ANFIS) in the intention reconsideration process of the agent model. Commitment strategy of the new intention reconsideration process is based on the motivation of the state transitions and the effect of belief changes in the environment.
Keywords :
adaptive systems; belief maintenance; containers; decision making; fuzzy reasoning; intelligent manufacturing systems; knowledge acquisition; learning (artificial intelligence); materials handling; strategic planning; BDI agent model; adaptive neurofuzzy inference system; belief changes; decision making dynamism; hybrid BDI architecture; hybrid intelligent agents; intention reconsideration process; knowledge acquisition model module; motivation based behavior; state transitions; strategic planning; supervised neural network; vessel assignment problems; vessel berthing applications; Adaptive systems; Containers; Decision making; Fuzzy neural networks; Fuzzy systems; Intelligent agent; Knowledge acquisition; Neural networks; Productivity; Strategic planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on
Print_ISBN :
0-7695-2291-2
Type :
conf
DOI :
10.1109/ICHIS.2004.6
Filename :
1409992
Link To Document :
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