• DocumentCode
    1023596
  • Title

    Molecular Verification of Rule-Based Systems Based on DNA Computation

  • Author

    Yeh, Chung-Wei ; Chu, Chih-Ping

  • Author_Institution
    Dept. of Comput. Sci. & Inf., Nat. Cheng Kung Univ., Tainan
  • Volume
    20
  • Issue
    7
  • fYear
    2008
  • fDate
    7/1/2008 12:00:00 AM
  • Firstpage
    965
  • Lastpage
    975
  • Abstract
    Various graphic techniques have been developed to analyze structural errors in rule-based systems that utilize inference (propositional) logic rules. Four typical errors in rule-based systems are: redundancy (numerous rule sets resulting in the same conclusion); circularity (a rule leading back to itself); incompleteness (deadends or a rule set conclusion leading to unreachable goals); and inconsistency (rules conflicting with each other). This study presents a new DNA-based computing algorithm mainly based upon Adleman´s DNA operations. It can be used to detect such errors. There are three phases to this molecular solution: rule-to-DNA transformation design, solution space generation, and rule verification. We first encode individual rules using relatively short DNA strands, and then generate all possible rule paths by the directed joining of such short strands to form longer strands. We then conduct the verification algorithm to detect errors. The potential of applying this proposed DNA computation algorithm to rule verification is promising given the operational time complexity of O(n*q), in which n denotes the number of fact clauses in the rule base and q is the number of rules with longest inference chain.
  • Keywords
    biocomputing; computational complexity; formal verification; inference mechanisms; knowledge based systems; knowledge verification; redundancy; DNA computation; graphic techniques; inference logic rules; molecular verification; redundancy; rule-based systems; time complexity; Evolutionary computing and genetic algorithms; Knowledge base verification; Rule-based processing;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2007.190743
  • Filename
    4415267