Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim

Mizraji Nathan, Eduardo Jacobo

Resumen:

Natural languages can express some logical propositions that humans are able to understand. We illustrate this fact with a famous text that Conan Doyle attributed to Holmes: "It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth". This is a subtle logical statement usually felt as an evident truth. The problem we are trying to solve is the cognitive reason for such a feeling. We postulate here that we accept Holmes' maxim as true because our adult brains are equipped with neural modules that naturally perform modal logical computations.


Los lenguajes naturales pueden expresar algunas proposiciones lógicas que los humanos pueden entender. Ilustramos esto con un famoso texto que Conan Doyle atribuye a Holmes: "Una vieja máxima mía dice que cuando has eliminado lo imposible, lo que queda, por muy improbable que parezca, tiene que ser la verdad”. Esto es una sutil declaración lógica que usualmente se siente evidentemente verdadera. El problema que tratamos de resolver es la razón cognitiva de tal sentimiento. Postulamos que aceptamos la máxima de Holmes como verdadera porque nuestros cerebros adultos están equipados con módulos neurales que ejecutan naturalmente cómputos de la lógica modal.


Detalles Bibliográficos
2016
Modal logics
Models of reasoning
Natural language
Neural computations
Computaciones neurales
Lenguaje natural
Modelos de razonamiento
Lógicas modales
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/25829
Acceso abierto
Licencia Creative Commons Atribución (CC - By 4.0)
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author Mizraji Nathan, Eduardo Jacobo
author_facet Mizraji Nathan, Eduardo Jacobo
author_role author
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dc.contributor.filiacion.none.fl_str_mv Mizraji Nathan Eduardo Jacobo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología
dc.creator.none.fl_str_mv Mizraji Nathan, Eduardo Jacobo
dc.date.accessioned.none.fl_str_mv 2020-11-06T16:26:13Z
dc.date.available.none.fl_str_mv 2020-11-06T16:26:13Z
dc.date.issued.none.fl_str_mv 2016
dc.description.abstract.none.fl_txt_mv Natural languages can express some logical propositions that humans are able to understand. We illustrate this fact with a famous text that Conan Doyle attributed to Holmes: "It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth". This is a subtle logical statement usually felt as an evident truth. The problem we are trying to solve is the cognitive reason for such a feeling. We postulate here that we accept Holmes' maxim as true because our adult brains are equipped with neural modules that naturally perform modal logical computations.
Los lenguajes naturales pueden expresar algunas proposiciones lógicas que los humanos pueden entender. Ilustramos esto con un famoso texto que Conan Doyle atribuye a Holmes: "Una vieja máxima mía dice que cuando has eliminado lo imposible, lo que queda, por muy improbable que parezca, tiene que ser la verdad”. Esto es una sutil declaración lógica que usualmente se siente evidentemente verdadera. El problema que tratamos de resolver es la razón cognitiva de tal sentimiento. Postulamos que aceptamos la máxima de Holmes como verdadera porque nuestros cerebros adultos están equipados con módulos neurales que ejecutan naturalmente cómputos de la lógica modal.
dc.format.extent.es.fl_str_mv 18 h.
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dc.identifier.citation.es.fl_str_mv Mizraji Nathan, E. "Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim". Theoria. [en línea] 2016, 31 (1): 7-25. doi: 10.1387/theoria.13959
dc.identifier.doi.none.fl_str_mv 10.1387/theoria.13959
dc.identifier.issn.none.fl_str_mv 0495-4548
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/25829
dc.language.iso.none.fl_str_mv en_US
eng
dc.publisher.es.fl_str_mv Universidad del Pais Vasco
dc.relation.ispartof.es.fl_str_mv Theoria, 2016, 31 (1): 7-25.
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución (CC - By 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.en.fl_str_mv Modal logics
Models of reasoning
Natural language
Neural computations
Computaciones neurales
Lenguaje natural
Modelos de razonamiento
Lógicas modales
dc.title.none.fl_str_mv Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
dc.type.es.fl_str_mv Artículo
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description Natural languages can express some logical propositions that humans are able to understand. We illustrate this fact with a famous text that Conan Doyle attributed to Holmes: "It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth". This is a subtle logical statement usually felt as an evident truth. The problem we are trying to solve is the cognitive reason for such a feeling. We postulate here that we accept Holmes' maxim as true because our adult brains are equipped with neural modules that naturally perform modal logical computations.
eu_rights_str_mv openAccess
format article
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identifier_str_mv Mizraji Nathan, E. "Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim". Theoria. [en línea] 2016, 31 (1): 7-25. doi: 10.1387/theoria.13959
0495-4548
10.1387/theoria.13959
instacron_str Universidad de la República
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instname_str Universidad de la República
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publishDate 2016
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución (CC - By 4.0)
spelling Mizraji Nathan Eduardo Jacobo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología2020-11-06T16:26:13Z2020-11-06T16:26:13Z2016Mizraji Nathan, E. "Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim". Theoria. [en línea] 2016, 31 (1): 7-25. doi: 10.1387/theoria.139590495-4548https://hdl.handle.net/20.500.12008/2582910.1387/theoria.13959Natural languages can express some logical propositions that humans are able to understand. We illustrate this fact with a famous text that Conan Doyle attributed to Holmes: "It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth". This is a subtle logical statement usually felt as an evident truth. The problem we are trying to solve is the cognitive reason for such a feeling. We postulate here that we accept Holmes' maxim as true because our adult brains are equipped with neural modules that naturally perform modal logical computations.Los lenguajes naturales pueden expresar algunas proposiciones lógicas que los humanos pueden entender. Ilustramos esto con un famoso texto que Conan Doyle atribuye a Holmes: "Una vieja máxima mía dice que cuando has eliminado lo imposible, lo que queda, por muy improbable que parezca, tiene que ser la verdad”. Esto es una sutil declaración lógica que usualmente se siente evidentemente verdadera. El problema que tratamos de resolver es la razón cognitiva de tal sentimiento. Postulamos que aceptamos la máxima de Holmes como verdadera porque nuestros cerebros adultos están equipados con módulos neurales que ejecutan naturalmente cómputos de la lógica modal.Submitted by Parodi Mónica (mparodi@fcien.edu.uy) on 2020-11-05T13:45:59Z No. of bitstreams: 2 license_rdf: 19875 bytes, checksum: 9fdbed07f52437945402c4e70fa4773e (MD5) 101387theoria13959.pdf: 476963 bytes, checksum: e9bf10fb49badae687092b3642d72b60 (MD5)Approved for entry into archive by Faget Cecilia (lfaget@fcien.edu.uy) on 2020-11-06T14:28:02Z (GMT) No. of bitstreams: 2 license_rdf: 19875 bytes, checksum: 9fdbed07f52437945402c4e70fa4773e (MD5) 101387theoria13959.pdf: 476963 bytes, checksum: e9bf10fb49badae687092b3642d72b60 (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@fic.edu.uy) on 2020-11-06T16:26:13Z (GMT). No. of bitstreams: 2 license_rdf: 19875 bytes, checksum: 9fdbed07f52437945402c4e70fa4773e (MD5) 101387theoria13959.pdf: 476963 bytes, checksum: e9bf10fb49badae687092b3642d72b60 (MD5) Previous issue date: 201618 h.application/pdfen_USengUniversidad del Pais VascoTheoria, 2016, 31 (1): 7-25.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución (CC - By 4.0)Modal logicsModels of reasoningNatural languageNeural computationsComputaciones neuralesLenguaje naturalModelos de razonamientoLógicas modalesIllustrating a neural model of logic computations: the case of Sherlock Holmes' old maximArtículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaMizraji Nathan, Eduardo JacoboLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/25829/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; charset=utf-844http://localhost:8080/xmlui/bitstream/20.500.12008/25829/2/license_urla0ebbeafb9d2ec7cbb19d7137ebc392cMD52license_textlicense_texttext/html; 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- Universidad de la Repúblicafalse
spellingShingle Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
Mizraji Nathan, Eduardo Jacobo
Modal logics
Models of reasoning
Natural language
Neural computations
Computaciones neurales
Lenguaje natural
Modelos de razonamiento
Lógicas modales
status_str publishedVersion
title Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
title_full Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
title_fullStr Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
title_full_unstemmed Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
title_short Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
title_sort Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
topic Modal logics
Models of reasoning
Natural language
Neural computations
Computaciones neurales
Lenguaje natural
Modelos de razonamiento
Lógicas modales
url https://hdl.handle.net/20.500.12008/25829