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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
16/02/1998 |
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Data da última atualização: |
12/12/2007 |
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Autoria: |
NICOLETTI, M. C.; MONARD, M. C. |
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Título: |
Constructing the extensional representation of an intensional domain theory in inductive logic programming. |
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Ano de publicação: |
1995 |
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Fonte/Imprenta: |
In: BRAZILIAN SYMPOSIUM ON ARTIFICIAL INTELLIGENCE, 12., 1995, Campinas. Advances in artificial intelligence: proceedings. Berlin: Springer, 1995. |
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Páginas: |
p.171-180 |
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Série: |
(Lecture Notes in Artificial Intelligence, 991; Lecture Notes in Computer Science). |
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ISBN: |
3-540-60436-7 |
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Idioma: |
Inglês |
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Notas: |
SBIA'95. Ed. by Jacques Wainer and Ariadne Carvalho. |
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Conteúdo: |
Introductive Logic Programming - ILP - is a new paradigm in the field of machine learning, which adopts the language or logic programs as a description language for the expression of instances, hipothesis and domain theory. Learning logical definitions requires the exploration of a very large space of hypothesis descriptions and, consequently, restrictions should be imposed on the hipothesis space to make learning a feasible task. In this work we discuss ways of confining the ILP hypothesis space by restricting the domain theory description language. Specially we focus on the notion of generative clauses, which enable the construction of a restricted form of horn clause program. In fact, the use of generative logic programs as description language allows for automatic transformation of the intensional expression of a domain theory into its extensional expression, as required by many existing ILP systems. We present an ILP environment which takes as input an intensional domain theory are generative, automatically constructs the extensional expression of this domain theory. We illustrate the use of this implemented environment through the ILP system GOLEM. |
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Palavras-Chave: |
Inteligencia artificial. |
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Thesaurus Nal: |
artificial intelligence. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01988naa a2200205 a 4500
001 1005960
005 2007-12-12
008 1995 bl uuuu u00u1 u #d
020 $a3-540-60436-7
100 1 $aNICOLETTI, M. C.
245 $aConstructing the extensional representation of an intensional domain theory in inductive logic programming.
260 $c1995
300 $ap.171-180
490 $a(Lecture Notes in Artificial Intelligence, 991; Lecture Notes in Computer Science).
500 $aSBIA'95. Ed. by Jacques Wainer and Ariadne Carvalho.
520 $aIntroductive Logic Programming - ILP - is a new paradigm in the field of machine learning, which adopts the language or logic programs as a description language for the expression of instances, hipothesis and domain theory. Learning logical definitions requires the exploration of a very large space of hypothesis descriptions and, consequently, restrictions should be imposed on the hipothesis space to make learning a feasible task. In this work we discuss ways of confining the ILP hypothesis space by restricting the domain theory description language. Specially we focus on the notion of generative clauses, which enable the construction of a restricted form of horn clause program. In fact, the use of generative logic programs as description language allows for automatic transformation of the intensional expression of a domain theory into its extensional expression, as required by many existing ILP systems. We present an ILP environment which takes as input an intensional domain theory are generative, automatically constructs the extensional expression of this domain theory. We illustrate the use of this implemented environment through the ILP system GOLEM.
650 $aartificial intelligence
653 $aInteligencia artificial
700 1 $aMONARD, M. C.
773 $tIn: BRAZILIAN SYMPOSIUM ON ARTIFICIAL INTELLIGENCE, 12., 1995, Campinas. Advances in artificial intelligence: proceedings. Berlin: Springer, 1995.
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Embrapa Agricultura Digital (CNPTIA) |
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