• 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