Journal article
Bias-Driven Revision of Logical Domain Theories
The Journal of artificial intelligence research, Vol.1, pp.159-208
01/01/1993
DOI: 10.1613/jair.27
Abstract
The theory revision problem is the problem of how best to go about revising a deficient domain theory using information contained in examples that expose inaccuracies. In this paper we present our approach to the theory revision problem for propositional domain theories. The approach described here, called PTR, uses probabilities associated with domain theory elements to numerically track the "flow'' of proof through the theory. This allows us to measure the precise role of a clause or literal in allowing or preventing a (desired or undesired) derivation for a given example. This information is used to efficiently locate and repair flawed elements of the theory. PTR is proved to converge to a theory which correctly classifies all examples, and shown experimentally to be fast and accurate even for deep theories.
Details
- Title: Subtitle
- Bias-Driven Revision of Logical Domain Theories
- Creators
- Moshe Koppel - Bar-Ilan UniversityRonen Feldman - Bar-Ilan UniversityAlberto Maria Segre - Cornell University
- Resource Type
- Journal article
- Publication Details
- The Journal of artificial intelligence research, Vol.1, pp.159-208
- DOI
- 10.1613/jair.27
- ISSN
- 1076-9757
- eISSN
- 1943-5037
- Publisher
- Ai Access Foundation
- Number of pages
- 50
- Grant note
- F30602-93-C-0018 / Air Force Office of Scientific Research; United States Department of Defense; Air Force Office of Scientific Research (AFOSR) N00014-90-J-1542 / Office of Naval Research
- Language
- English
- Date published
- 01/01/1993
- Academic Unit
- Nursing; Fraternal Order of Eagles Diabetes Research Center; Computer Science
- Record Identifier
- 9984259411002771
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