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020 _a9783540690498
_9978-3-540-69049-8
024 7 _a10.1007/3-540-62927-0
_2doi
050 4 _aQA76.758
072 7 _aUMZ
_2bicssc
072 7 _aCOM051230
_2bisacsh
072 7 _aUMZ
_2thema
082 0 4 _a005.1
_223
100 1 _aNienhuys-Cheng, Shan-Hwei.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aFoundations of Inductive Logic Programming
_h[electronic resource] /
_cby Shan-Hwei Nienhuys-Cheng, Ronald de Wolf.
250 _a1st ed. 1997.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c1997.
300 _aXVIII, 410 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1228
505 0 _aPropositional logic -- First-order logic -- Normal forms and Herbrand models -- Resolution -- Subsumption theorem and refutation completeness -- Linear and input resolution -- SLD-resolution -- SLDNF-resolution -- What is inductive logic programming? -- The framework for model inference -- Inverse resolution -- Unfolding -- The lattice and cover structure of atoms -- The subsumption order -- The implication order -- Background knowledge -- Refinement operators -- PAC learning -- Further topics.
520 _aInductive Logic Programming is a young and rapidly growing field combining machine learning and logic programming. This self-contained tutorial is the first theoretical introduction to ILP; it provides the reader with a rigorous and sufficiently broad basis for future research in the area. In the first part, a thorough treatment of first-order logic, resolution-based theorem proving, and logic programming is given. The second part introduces the main concepts of ILP and systematically develops the most important results on model inference, inverse resolution, unfolding, refinement operators, least generalizations, and ways to deal with background knowledge. Furthermore, the authors give an overview of PAC learning results in ILP and of some of the most relevant implemented systems.
650 0 _aSoftware engineering.
650 0 _aArtificial intelligence.
650 0 _aMachine theory.
650 0 _aComputer programming.
650 1 4 _aSoftware Engineering.
650 2 4 _aArtificial Intelligence.
650 2 4 _aFormal Languages and Automata Theory.
650 2 4 _aProgramming Techniques.
700 1 _aWolf, Ronald de.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540629276
776 0 8 _iPrinted edition:
_z9783662174852
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1228
856 4 0 _uhttps://doi.org/10.1007/3-540-62927-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
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942 _cSPRINGER
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