Conference Paper

An Evolutionary Optimization Approach to Cost-Based Abduction, with Comparison to PSO

Univ. of North Carolina in Washington, Washington
DOI: 10.1109/IJCNN.2007.4371425 Conference: Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Source: IEEE Xplore

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 apply an evolutionary algorithm (EA) to the problem of finding least-cost proofs in cost-based abduction systems, comparing performance to PSO using a difficult problem instance.

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