Illustrating a neural model of logic computations: the case of Sherlock Holmes' old maxim
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.
2016 | |
Modal logics Models of reasoning Natural language Neural computations Computaciones neurales Lenguaje natural Modelos de razonamiento Lógicas modales |
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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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collection | COLIBRI |
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. |
dc.format.mimetype.en.fl_str_mv | application/pdf |
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 |
id | COLIBRI_a6fccb3c4e62380ca3273d8891935834 |
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 |
institution | Universidad de la República |
instname_str | Universidad de la República |
language | eng |
language_invalid_str_mv | en_US |
network_acronym_str | COLIBRI |
network_name_str | COLIBRI |
oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/25829 |
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 |