Abduction and induction are strictly related forms of defeasible reason- ing. However, Machine Learning research is mainly focused on inductive techniques,leading from specific examples to general rules, with applica- tions to classification, diagnosis and program synthesis. Abduction has been used in Machine Learning, but its use was typically an aside tech- nique, to be integrated or added on top of the basic inductive scheme. We discuss the general relation between abductive and inductive reason- ing, showing that they solve different instantiations of the same problem. Then we analyze the specific ways abduction has been used in Machine Learning. Two different cases are individuated:(1) abductive reasoning used in explanation-based learning systems as a heuristic to guide search in top-down specialization, and (2) abduction used fo generating missing examples in relational learning. In both cases,the use of abduction is not general and adapted to a very tiny and specific problem. In this sense, the Machine Learning community has not used abduction as a synonym of induction, despite the high degree of similarity. However, both uses of abduction in learning have been proved to be effective for their intended purposes.

Abduction in Machine Learning

BERGADANO, Francesco;GUNETTI, Daniele
2000-01-01

Abstract

Abduction and induction are strictly related forms of defeasible reason- ing. However, Machine Learning research is mainly focused on inductive techniques,leading from specific examples to general rules, with applica- tions to classification, diagnosis and program synthesis. Abduction has been used in Machine Learning, but its use was typically an aside tech- nique, to be integrated or added on top of the basic inductive scheme. We discuss the general relation between abductive and inductive reason- ing, showing that they solve different instantiations of the same problem. Then we analyze the specific ways abduction has been used in Machine Learning. Two different cases are individuated:(1) abductive reasoning used in explanation-based learning systems as a heuristic to guide search in top-down specialization, and (2) abduction used fo generating missing examples in relational learning. In both cases,the use of abduction is not general and adapted to a very tiny and specific problem. In this sense, the Machine Learning community has not used abduction as a synonym of induction, despite the high degree of similarity. However, both uses of abduction in learning have been proved to be effective for their intended purposes.
Handbook of Defasible Reasoning and Uncertainty Management Systems, Vol 4: Abductive Reasoning and Learning
Kluwer Academic Publishers
4
197
229
0792365658
Artificial Intelligence; Machine Learning; Abduction
Bergadano F.; Cutello V.; Gunetti D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/122311
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