From Natural to Artificial Intelligence: Numerical processing for cognitive tasks
Identifieur interne : 002463 ( Hal/Curation ); précédent : 002462; suivant : 002464From Natural to Artificial Intelligence: Numerical processing for cognitive tasks
Auteurs : Frédéric Alexandre [France] ; Hervé Frezza-Buet [France]Source :
Descripteurs français
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- topic : économie.
Abstract
Cognitive modeling can be derived from expert knowledge integration or experimental data analysis. This chapter introduces these two main ways of modeling and concentrates on the latter aspect and the related numerical tools together with their possible role. More precisely, the evolutionary approach is presented for optimization and tuning, artificial neural networks for associative reasoning and the stochastic approach for planning. We then conclude on the need for a modular framework, integrating these numerical and other symbolic tools.
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or experimental data analysis. This chapter introduces these two main ways of modeling and concentrates on the latter aspect and the related numerical tools together with their possible role. More precisely, the evolutionary approach is presented for optimization and tuning, artificial neural networks for associative reasoning and the stochastic approach for planning. We then conclude on the need for a modular framework, integrating these numerical and other symbolic tools.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">From Natural to Artificial Intelligence: Numerical processing for cognitive tasks</title><author role="aut"><persName><forename type="first">Frédéric</forename><surname>Alexandre</surname></persName><email>Frederic.Alexandre@inria.fr</email><idno type="idhal">frederic-alexandre</idno><idno type="halauthor">778506</idno><orgName ref="#struct-300009"></orgName><affiliation ref="#struct-2348"></affiliation></author><author role="aut"><persName><forename type="first">Hervé</forename><surname>Frezza-Buet</surname></persName><email></email><idno type="idhal">herve-frezza-buet</idno><idno type="halauthor">131155</idno><orgName ref="#struct-364926"></orgName><affiliation ref="#struct-2348"></affiliation></author><editor role="depositor"><persName><forename>Publications</forename><surname>Loria</surname></persName><email>publications@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2006-09-26 10:12:56</date><date type="whenModified">2016-05-19 01:09:36</date><date type="whenReleased">2006-09-28 15:22:46</date><date type="whenProduced">2004</date></edition><respStmt><resp>contributor</resp><name key="108626"><persName><forename>Publications</forename><surname>Loria</surname></persName><email>publications@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00099961</idno><idno type="halUri">https://hal.inria.fr/inria-00099961</idno><idno type="halBibtex">alexandre:inria-00099961</idno><idno type="halRefHtml">Paul Bourgine and Jean-Pierre Nadal. Cognitive Economics, Springer, pp.113-130, 2004</idno><idno type="halRef">Paul Bourgine and Jean-Pierre Nadal. Cognitive Economics, Springer, pp.113-130, 2004</idno></publicationStmt><seriesStmt><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA-CSAI" p="LORIA">Systèmes complexes et intelligence artificielle</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno></seriesStmt><notesStmt><note type="commentary">Contribution à un ouvrage.</note><note type="audience" n="0">Not set</note><note type="popular" n="0">No</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">From Natural to Artificial Intelligence: Numerical processing for cognitive tasks</title><author role="aut"><persName><forename type="first">Frédéric</forename><surname>Alexandre</surname></persName><email>Frederic.Alexandre@inria.fr</email><idno type="idHal">frederic-alexandre</idno><idno type="halAuthorId">778506</idno><orgName ref="#struct-300009"></orgName><affiliation ref="#struct-2348"></affiliation></author><author role="aut"><persName><forename type="first">Hervé</forename><surname>Frezza-Buet</surname></persName><idno type="idHal">herve-frezza-buet</idno><idno type="halAuthorId">131155</idno><orgName ref="#struct-364926"></orgName><affiliation ref="#struct-2348"></affiliation></author></analytic><monogr><idno type="localRef">A03-R-323 || alexandre03a</idno><title level="m">Cognitive Economics</title><editor>Paul Bourgine and Jean-Pierre Nadal</editor><imprint><publisher>Springer</publisher><biblScope unit="pp">113-130</biblScope><date type="datePub">2004</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="fr">reinforcement</term><term xml:lang="fr">cognition</term><term xml:lang="fr">economics</term><term xml:lang="fr">artificial neural networks</term><term xml:lang="fr">evolutionary approach</term><term xml:lang="fr">économie</term><term xml:lang="fr">réseaux de neurones artificiels</term><term xml:lang="fr">approche évolutionnaire</term><term xml:lang="fr">renforcement</term></keywords><classCode scheme="halDomain" n="info.info-oh">Computer Science [cs]/Other [cs.OH]</classCode><classCode scheme="halTypology" n="COUV">Book section</classCode></textClass><abstract xml:lang="en">Cognitive modeling can be derived from expert knowledge integration or experimental data analysis. This chapter introduces these two main ways of modeling and concentrates on the latter aspect and the related numerical tools together with their possible role. More precisely, the evolutionary approach is presented for optimization and tuning, artificial neural networks for associative reasoning and the stochastic approach for planning. We then conclude on the need for a modular framework, integrating these numerical and other symbolic tools.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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