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On potential cognitive abilities in the machine kingdom

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On potential cognitive abilities in the machine kingdom

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dc.contributor.author Hernández-Orallo, José es_ES
dc.contributor.author Dowe, David L. es_ES
dc.date.accessioned 2014-09-22T17:48:05Z
dc.date.available 2014-09-22T17:48:05Z
dc.date.issued 2013-05
dc.identifier.issn 0924-6495
dc.identifier.uri http://hdl.handle.net/10251/39847
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/s11023-012-9299-6 es_ES
dc.description.abstract Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be different for the ‘machine kingdom’. While machines can be characterised by a set of cognitive abilities, and measuring them is already a big challenge, known as ‘universal psychometrics’, a more informative, and yet more challenging, goal would be to also determine the potential cognitive abilities of a machine. In this paper we investigate the notion of potential cognitive ability for machines, focussing especially on universality and intelligence. We consider several machine characterisations (non-interactive and interactive) and give definitions for each case, considering permanent and temporal potentials. From these definitions, we analyse the relation between some potential abilities, we bring out the dependency on the environment distribution and we suggest some ideas about how potential abilities can be measured. Finally, we also analyse the potential of environments at different levels and briefly discuss whether machines should be designed to be intelligent or potentially intelligent. es_ES
dc.description.sponsorship We thank the anonymous reviewers for their comments, which have helped to significantly improve this paper. This work was supported by the MEC-MINECO projects CONSOLIDER-INGENIO CSD2007-00022 and TIN 2010-21062-C02-02, GVA project PROMETEO/2008/051, the COST - European Cooperation in the field of Scientific and Technical Research IC0801 AT. Finally, we thank three pioneers ahead of their time(s). We thank Ray Solomonoff (1926-2009) and Chris Wallace (1933-2004) for all that they taught us, directly and indirectly. And, in his centenary year, we thank Alan Turing (1912-1954), with whom it perhaps all began. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Minds and Machines es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Cognitive abilities es_ES
dc.subject Machine intelligence measurement es_ES
dc.subject Turing machines es_ES
dc.subject Universality probability es_ES
dc.subject Potential intelligence es_ES
dc.subject Psychometrics es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title On potential cognitive abilities in the machine kingdom es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11023-012-9299-6
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CSD2007-00022/ES/Agreement Technologies/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/COST//IC0801/EU/Agreement Technologies/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2010-21062-C02-02/ES/SWEETLOGICS-UPV/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO08%2F2008%2F051/ES/Advances on Agreement Technologies for Computational Entities (atforce)/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Hernández-Orallo, J.; Dowe, DL. (2013). On potential cognitive abilities in the machine kingdom. Minds and Machines. 23(2):179-210. https://doi.org/10.1007/s11023-012-9299-6 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://link.springer.com/article/10.1007%2Fs11023-012-9299-6 es_ES
dc.description.upvformatpinicio 179 es_ES
dc.description.upvformatpfin 210 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 23 es_ES
dc.description.issue 2 es_ES
dc.relation.senia 263077
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Educación y Ciencia es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder European Cooperation in Science and Technology
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