dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:21:41Z
dc.date.accessioned2022-10-05T17:58:33Z
dc.date.available2014-05-27T11:21:41Z
dc.date.available2022-10-05T17:58:33Z
dc.date.created2014-05-27T11:21:41Z
dc.date.issued2005-12-01
dc.identifierPragmatics and Cognition, v. 13, n. 3, p. 565-582, 2005.
dc.identifier0929-0907
dc.identifier1569-9943
dc.identifierhttp://hdl.handle.net/11449/68509
dc.identifier10.1075/pc.13.3.09qui
dc.identifier2-s2.0-30144441545
dc.identifier1279824839196223
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3918042
dc.description.abstractThe impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments. © John Benjamins Publishing Company.
dc.languageeng
dc.relationPragmatics and Cognition
dc.relation0.370
dc.relation0,146
dc.relation0,146
dc.rightsAcesso restrito
dc.sourceScopus
dc.subjectAffordances
dc.subjectDynamical systems
dc.subjectIntelligence
dc.subjectMeaningful information
dc.subjectMechanicism
dc.subjectMutuality
dc.subjectOrder parameters
dc.subjectRobotics
dc.subjectSelf-organization
dc.subjectTechnology
dc.titleInformation and mechanical models of intelligence: What can we learn from cognitive science?
dc.typeArtigo


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