• DocumentCode
    2755118
  • Title

    Finding Least Cost Proofs Using a Hierarchical PSO

  • Author

    Chivers, Shawn T. ; Tagliarini, Gene A. ; Abdelbar, Ashraf M.

  • Author_Institution
    Dept. of Comput. Sci., North Carolina Univ., Wilmington, NC
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    156
  • Lastpage
    161
  • Abstract
    Abduction is the process of proceeding from data describing a set of observations or events, to a set of hypotheses which best explains or accounts for the data. Cost-based abduction (CBA) is a formalism in which evidence to be explained is treated as a goal to be proven, proofs have costs based on how much needs to be assumed to complete the proof, and the set of assumptions needed to complete the least-cost proof are taken as the best explanation for the given evidence. In this paper, we explore using a hierarchical PSO to find least-cost proofs in cost-based abduction systems, comparing performance to simulated annealing using a difficult problem instance.
  • Keywords
    particle swarm optimisation; cost-based abduction; hierarchical particle swarm optimization; least cost proofs; Computational modeling; Computer science; Cost function; Functional programming; Integer linear programming; Integrated circuit modeling; Logic programming; Particle swarm optimization; Polynomials; Simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Swarm Intelligence Symposium, 2007. SIS 2007. IEEE
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0708-7
  • Type

    conf

  • DOI
    10.1109/SIS.2007.368040
  • Filename
    4223169