KittyCat: a cognitive model of structure-form discovery
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | http://hdl.handle.net/10438/12442 |
Resumo: | Cognition is a core subject to understand how humans think and behave. In that sense, it is clear that Cognition is a great ally to Management, as the later deals with people and is very interested in how they behave, think, and make decisions. However, even though Cognition shows great promise as a field, there are still many topics to be explored and learned in this fairly new area. Kemp & Tenembaum (2008) tried to a model graph-structure problem in which, given a dataset, the best underlying structure and form would emerge from said dataset by using bayesian probabilistic inferences. This work is very interesting because it addresses a key cognition problem: learning. According to the authors, analogous insights and discoveries, understanding the relationships of elements and how they are organized, play a very important part in cognitive development. That is, this are very basic phenomena that allow learning. Human beings minds do not function as computer that uses bayesian probabilistic inferences. People seem to think differently. Thus, we present a cognitively inspired method, KittyCat, based on FARG computer models (like Copycat and Numbo), to solve the proposed problem of discovery the underlying structural-form of a dataset. |
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Sodré, Andréia Brandão DaltroEscolas::EBAPESobral, FilipeKoiller, JairLinhares, Alexandre2014-11-17T11:35:31Z2014-11-17T11:35:31Z2014-10-09SODRÉ, Andréia Brandão Daltro. KittyCat: a cognitive model of structure-form discovery. Dissertação (Mestrado em Administração) - Escola Brasileira de Administração Pública e de Empresas, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2014.http://hdl.handle.net/10438/12442Cognition is a core subject to understand how humans think and behave. In that sense, it is clear that Cognition is a great ally to Management, as the later deals with people and is very interested in how they behave, think, and make decisions. However, even though Cognition shows great promise as a field, there are still many topics to be explored and learned in this fairly new area. Kemp & Tenembaum (2008) tried to a model graph-structure problem in which, given a dataset, the best underlying structure and form would emerge from said dataset by using bayesian probabilistic inferences. This work is very interesting because it addresses a key cognition problem: learning. According to the authors, analogous insights and discoveries, understanding the relationships of elements and how they are organized, play a very important part in cognitive development. That is, this are very basic phenomena that allow learning. Human beings minds do not function as computer that uses bayesian probabilistic inferences. People seem to think differently. Thus, we present a cognitively inspired method, KittyCat, based on FARG computer models (like Copycat and Numbo), to solve the proposed problem of discovery the underlying structural-form of a dataset.engCognitionCognitive-modelStructural-form discoveryFARGKemp, CharlesTenenbaum, Joshua B.Administração de empresasCogniçãoDesenvolvimento cognitivoAprendizagem organizacionalProbabilidadesTenenbaum, Joshua B.Kemp, CharlesKittyCat: a cognitive model of structure-form discoveryinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessORIGINALDissertacao_Andreia Upload.pdfDissertacao_Andreia Upload.pdfDissertação de Mestradoapplication/pdf1696600https://repositorio.fgv.br/bitstreams/d628d8c2-b648-4503-a450-807c17df6104/downloada36857c678f55a7f75214bfa5d34414fMD51LICENSElicense.txtlicense.txttext/plain; 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|
dc.title.eng.fl_str_mv |
KittyCat: a cognitive model of structure-form discovery |
title |
KittyCat: a cognitive model of structure-form discovery |
spellingShingle |
KittyCat: a cognitive model of structure-form discovery Sodré, Andréia Brandão Daltro Cognition Cognitive-model Structural-form discovery FARG Kemp, Charles Tenenbaum, Joshua B. Administração de empresas Cognição Desenvolvimento cognitivo Aprendizagem organizacional Probabilidades Tenenbaum, Joshua B. Kemp, Charles |
title_short |
KittyCat: a cognitive model of structure-form discovery |
title_full |
KittyCat: a cognitive model of structure-form discovery |
title_fullStr |
KittyCat: a cognitive model of structure-form discovery |
title_full_unstemmed |
KittyCat: a cognitive model of structure-form discovery |
title_sort |
KittyCat: a cognitive model of structure-form discovery |
author |
Sodré, Andréia Brandão Daltro |
author_facet |
Sodré, Andréia Brandão Daltro |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EBAPE |
dc.contributor.member.none.fl_str_mv |
Sobral, Filipe Koiller, Jair |
dc.contributor.author.fl_str_mv |
Sodré, Andréia Brandão Daltro |
dc.contributor.advisor1.fl_str_mv |
Linhares, Alexandre |
contributor_str_mv |
Linhares, Alexandre |
dc.subject.eng.fl_str_mv |
Cognition Cognitive-model Structural-form discovery |
topic |
Cognition Cognitive-model Structural-form discovery FARG Kemp, Charles Tenenbaum, Joshua B. Administração de empresas Cognição Desenvolvimento cognitivo Aprendizagem organizacional Probabilidades Tenenbaum, Joshua B. Kemp, Charles |
dc.subject.por.fl_str_mv |
FARG Kemp, Charles Tenenbaum, Joshua B. |
dc.subject.area.por.fl_str_mv |
Administração de empresas |
dc.subject.bibliodata.por.fl_str_mv |
Cognição Desenvolvimento cognitivo Aprendizagem organizacional Probabilidades Tenenbaum, Joshua B. Kemp, Charles |
description |
Cognition is a core subject to understand how humans think and behave. In that sense, it is clear that Cognition is a great ally to Management, as the later deals with people and is very interested in how they behave, think, and make decisions. However, even though Cognition shows great promise as a field, there are still many topics to be explored and learned in this fairly new area. Kemp & Tenembaum (2008) tried to a model graph-structure problem in which, given a dataset, the best underlying structure and form would emerge from said dataset by using bayesian probabilistic inferences. This work is very interesting because it addresses a key cognition problem: learning. According to the authors, analogous insights and discoveries, understanding the relationships of elements and how they are organized, play a very important part in cognitive development. That is, this are very basic phenomena that allow learning. Human beings minds do not function as computer that uses bayesian probabilistic inferences. People seem to think differently. Thus, we present a cognitively inspired method, KittyCat, based on FARG computer models (like Copycat and Numbo), to solve the proposed problem of discovery the underlying structural-form of a dataset. |
publishDate |
2014 |
dc.date.accessioned.fl_str_mv |
2014-11-17T11:35:31Z |
dc.date.available.fl_str_mv |
2014-11-17T11:35:31Z |
dc.date.issued.fl_str_mv |
2014-10-09 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SODRÉ, Andréia Brandão Daltro. KittyCat: a cognitive model of structure-form discovery. Dissertação (Mestrado em Administração) - Escola Brasileira de Administração Pública e de Empresas, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2014. |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10438/12442 |
identifier_str_mv |
SODRÉ, Andréia Brandão Daltro. KittyCat: a cognitive model of structure-form discovery. Dissertação (Mestrado em Administração) - Escola Brasileira de Administração Pública e de Empresas, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2014. |
url |
http://hdl.handle.net/10438/12442 |
dc.language.iso.fl_str_mv |
eng |
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eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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