DocumentCode
1844558
Title
ERPBAM: A Model for Structure and Reasoning of Agent Based on Entity-Relation-Problem Knowledge Representation System
Author
Chen, Xue-Long ; Li, Li-Ming ; Wang, Yan-Zhang ; Wang, Ning ; Ye, Xin
Volume
3
fYear
2009
fDate
15-18 Sept. 2009
Firstpage
365
Lastpage
368
Abstract
At first, a new knowledge representation system, named entity-relation-problem (E-R-P) knowledge representation system, is proposed. Then a model for structure and reasoning of agent based on the E-R-P knowledge representation system, named ERPBAM, is put forward. ERPBAM is straightforward, flexible and general. So it solves the problem of complexity of structure and reasoning for agent, which is caused by complex symbol representation and deduction. Furthermore, ERPBAM has the ability to handle all kinds of information, especially the fuzzy information, involved in the reasoning process. Because E-R-P knowledge representation system synthetically represents the knowledge of objective system and realistic problems, the structure and reasoning process of agent in ERPBAM become more integrated, and the corresponding implementation code becomes more compact.
Keywords
Fuzzy reasoning; Humans; Intelligent agent; Intelligent structures; Knowledge representation; Logic; Object oriented modeling; Problem-solving; Production systems; Semantic Web; agent; entity-relation-problem; knowledge representation; reasoning; structure;
fLanguage
English
Publisher
iet
Conference_Titel
Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
Conference_Location
Milan, Italy
Print_ISBN
978-0-7695-3801-3
Electronic_ISBN
978-1-4244-5331-3
Type
conf
DOI
10.1109/WI-IAT.2009.302
Filename
5285068
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