A model for generalization based on confirmatory induction
Identifieur interne :
000C48 ( PascalFrancis/Corpus );
précédent :
000C47;
suivant :
000C49
A model for generalization based on confirmatory induction
Auteurs : N. Lachiche ;
P. MarquisSource :
-
Lecture notes in computer science [ 0302-9743 ] ; 1997.
RBID : Pascal:97-0390502
Descripteurs français
English descriptors
Abstract
Confirmatory induction is based on the assumption that unknown individuals are similar to known ones, i.e. they satisfy the properties shared by known individuals. This assumption can be represented inside a non-monotonic logical framework. Accordingly, existing approaches to confirmatory induction take advantage of the machinery developed so far for non-monotonic inference. However, they are based on completion policies that are unnecessary strong for the induction purpose. The contribution of this paper is twofold: some basic requirements that any model for generalization based on confirmatory induction should satisfy are proposed. Then, a model for generalization based on Hempel's notion of confirmation is introduced. This model is rational in the sense that it satisfies the rationality postulates we exhibit; moreover, the completion principle on which this model is based captures exactly the similarity assumption, hence the model can be considered minimal as well.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
| pA |
| A01 | 01 | 1 | | @0 0302-9743 |
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| A05 | | | | @2 1224 |
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| A08 | 01 | 1 | ENG | @1 A model for generalization based on confirmatory induction |
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| A09 | 01 | 1 | ENG | @1 Machine learning : Prague, April 23-25, 1997 |
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| A11 | 01 | 1 | | @1 LACHICHE (N.) |
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| A11 | 02 | 1 | | @1 MARQUIS (P.) |
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| A12 | 01 | 1 | | @1 SOMEREN (Maarten van) @9 ed. |
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| A12 | 02 | 1 | | @1 WIDMER (Gerhard) @9 ed. |
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| A14 | 01 | | | @1 CRIN/CNRS - INRIA Lorraine, Bâtiment LORIA, Campus scientifique B.P. 239 @2 54506 Vandœuvre-lès-Nancy @3 FRA @Z 1 aut. |
|---|
| A14 | 02 | | | @1 CRIL/Université d'Artois, Rue de l'Université, S.P. 16 @2 62307 Lens @3 FRA @Z 2 aut. |
|---|
| A20 | | | | @1 154-161 |
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| A21 | | | | @1 1997 |
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| A23 | 01 | | | @0 ENG |
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| A43 | 01 | | | @1 INIST @2 16343 @5 354000062524650130 |
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| A44 | | | | @0 0000 @1 © 1997 INIST-CNRS. All rights reserved. |
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| A45 | | | | @0 19 ref. |
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| A47 | 01 | 1 | | @0 97-0390502 |
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| A60 | | | | @1 P @2 C |
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| A61 | | | | @0 A |
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| A64 | 01 | 1 | | @0 Lecture notes in computer science |
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| A66 | 01 | | | @0 DEU |
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| A66 | 02 | | | @0 USA |
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| C01 | 01 | | ENG | @0 Confirmatory induction is based on the assumption that unknown individuals are similar to known ones, i.e. they satisfy the properties shared by known individuals. This assumption can be represented inside a non-monotonic logical framework. Accordingly, existing approaches to confirmatory induction take advantage of the machinery developed so far for non-monotonic inference. However, they are based on completion policies that are unnecessary strong for the induction purpose. The contribution of this paper is twofold: some basic requirements that any model for generalization based on confirmatory induction should satisfy are proposed. Then, a model for generalization based on Hempel's notion of confirmation is introduced. This model is rational in the sense that it satisfies the rationality postulates we exhibit; moreover, the completion principle on which this model is based captures exactly the similarity assumption, hence the model can be considered minimal as well. |
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| C02 | 01 | X | | @0 001D02C02 |
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| C03 | 01 | X | FRE | @0 Intelligence artificielle @5 01 |
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| C03 | 01 | X | ENG | @0 Artificial intelligence @5 01 |
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| C03 | 01 | X | SPA | @0 Inteligencia artificial @5 01 |
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| C03 | 02 | X | FRE | @0 Algorithme apprentissage @5 02 |
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| C03 | 02 | X | ENG | @0 Learning algorithm @5 02 |
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| C03 | 02 | X | SPA | @0 Algoritmo aprendizaje @5 02 |
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| C03 | 03 | X | FRE | @0 Circonscription @5 03 |
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| N21 | | | | @1 237 |
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| pR |
| A30 | 01 | 1 | ENG | @1 ECML-97 : European conference on machine learning @2 9 @3 Prague CZE @4 1997-04-23 |
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Format Inist (serveur)
| NO : | PASCAL 97-0390502 INIST |
|---|
| ET : | A model for generalization based on confirmatory induction |
|---|
| AU : | LACHICHE (N.); MARQUIS (P.); SOMEREN (Maarten van); WIDMER (Gerhard) |
|---|
| AF : | CRIN/CNRS - INRIA Lorraine, Bâtiment LORIA, Campus scientifique B.P. 239/54506 Vandœuvre-lès-Nancy/France (1 aut.); CRIL/Université d'Artois, Rue de l'Université, S.P. 16/62307 Lens/France (2 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 1997; Vol. 1224; Pp. 154-161; Bibl. 19 ref. |
|---|
| LA : | Anglais |
|---|
| EA : | Confirmatory induction is based on the assumption that unknown individuals are similar to known ones, i.e. they satisfy the properties shared by known individuals. This assumption can be represented inside a non-monotonic logical framework. Accordingly, existing approaches to confirmatory induction take advantage of the machinery developed so far for non-monotonic inference. However, they are based on completion policies that are unnecessary strong for the induction purpose. The contribution of this paper is twofold: some basic requirements that any model for generalization based on confirmatory induction should satisfy are proposed. Then, a model for generalization based on Hempel's notion of confirmation is introduced. This model is rational in the sense that it satisfies the rationality postulates we exhibit; moreover, the completion principle on which this model is based captures exactly the similarity assumption, hence the model can be considered minimal as well. |
|---|
| CC : | 001D02C02 |
|---|
| FD : | Intelligence artificielle; Algorithme apprentissage; Circonscription |
|---|
| ED : | Artificial intelligence; Learning algorithm; Circumscription |
|---|
| SD : | Inteligencia artificial; Algoritmo aprendizaje; Circonscripción |
|---|
| LO : | INIST-16343.354000062524650130 |
|---|
| ID : | 97-0390502 |
|---|
Links to Exploration step
Pascal:97-0390502
Le document en format XML
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</keywords><front><div type="abstract" xml:lang="en">Confirmatory induction is based on the assumption that unknown individuals are similar to known ones, i.e. they satisfy the properties shared by known individuals. This assumption can be represented inside a non-monotonic logical framework. Accordingly, existing approaches to confirmatory induction take advantage of the machinery developed so far for non-monotonic inference. However, they are based on completion policies that are unnecessary strong for the induction purpose. The contribution of this paper is twofold: some basic requirements that any model for generalization based on confirmatory induction should satisfy are proposed. Then, a model for generalization based on Hempel's notion of confirmation is introduced. This model is rational in the sense that it satisfies the rationality postulates we exhibit; moreover, the completion principle on which this model is based captures exactly the similarity assumption, hence the model can be considered minimal as well.</div>
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<ET>A model for generalization based on confirmatory induction</ET>
<AU>LACHICHE (N.); MARQUIS (P.); SOMEREN (Maarten van); WIDMER (Gerhard)</AU>
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<EA>Confirmatory induction is based on the assumption that unknown individuals are similar to known ones, i.e. they satisfy the properties shared by known individuals. This assumption can be represented inside a non-monotonic logical framework. Accordingly, existing approaches to confirmatory induction take advantage of the machinery developed so far for non-monotonic inference. However, they are based on completion policies that are unnecessary strong for the induction purpose. The contribution of this paper is twofold: some basic requirements that any model for generalization based on confirmatory induction should satisfy are proposed. Then, a model for generalization based on Hempel's notion of confirmation is introduced. This model is rational in the sense that it satisfies the rationality postulates we exhibit; moreover, the completion principle on which this model is based captures exactly the similarity assumption, hence the model can be considered minimal as well.</EA>
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