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
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;
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
DOI :
10.1109/WI-IAT.2009.302