Top-down algorithms for relational learning specialize general rules un- til they are consistent , and are guided by heuristics of different kinds.In general, a correct solutiion is not guaranteed. By contrast, bottom-up methods are well formalized, usually within the framework of inverse reso- lution.Inverse resolution has also been used as an efficient tool for deduc- tive reasoning, and here we prove tha input refutations can be translated into inverse unit refutations.This result allows us to show that top-down learning methods can be also described by means of inverse resolution, yielding a unified theory of relational learning.

Learning Relations: Basing Top-Down Methods on Inverse Resolution

BERGADANO, Francesco;GUNETTI, Daniele
1993-01-01

Abstract

Top-down algorithms for relational learning specialize general rules un- til they are consistent , and are guided by heuristics of different kinds.In general, a correct solutiion is not guaranteed. By contrast, bottom-up methods are well formalized, usually within the framework of inverse reso- lution.Inverse resolution has also been used as an efficient tool for deduc- tive reasoning, and here we prove tha input refutations can be translated into inverse unit refutations.This result allows us to show that top-down learning methods can be also described by means of inverse resolution, yielding a unified theory of relational learning.
1993
Advances in Artificial Intelligence
Springer-Verlag
LNAI 728
190
201
3540572929
Artificial Intelligence; Machine Learning; Inductive Logic Programming
Bergadano F.; Gunetti D.
File in questo prodotto:
File Dimensione Formato  
aiia93.pdf

Accesso aperto

Tipo di file: PREPRINT (PRIMA BOZZA)
Dimensione 162.57 kB
Formato Adobe PDF
162.57 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/124871
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact