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
Link To Document :
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