Computer models solving intelligence test problems: progress and implications

José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe

    Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

    Abstract

    While some computational models of intelligence test problems were proposed throughout the second half of the XXth century, in the first years of the XXIst century we have seen an increasing number of computer systems being able to score well on particular intelligence test tasks. However, despite this increasing trend there has been no general account of all these works in terms of how they relate to each other and what their real achievements are. In this paper, we provide some insight on these issues by giving a comprehensive account of about thirty computer models, from the 1960s to nowadays, and their relationships, focussing on the range of intelligence test tasks they address, the purpose of the models, how general or specialised these models are, the AI techniques they use in each case, their comparison with human performance, and their evaluation of item difficulty.

    Original languageEnglish
    Title of host publicationProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
    EditorsCarles Sierra
    Place of PublicationCalifornia USA
    PublisherInternational Joint Conferences on Artificial Intelligence
    Pages5005-5009
    Number of pages5
    ISBN (Print)9780999241103
    Publication statusPublished - 2017
    EventInternational Joint Conference on Artificial Intelligence 2017 - Melbourne, Australia
    Duration: 19 Aug 201725 Aug 2017
    Conference number: 26th
    https://ijcai-17.org/

    Conference

    ConferenceInternational Joint Conference on Artificial Intelligence 2017
    Abbreviated titleIJCAI 2017
    CountryAustralia
    CityMelbourne
    Period19/08/1725/08/17
    Internet address

    Cite this

    Hernández-Orallo, J., Martínez-Plumed, F., Schmid, U., Siebers, M., & Dowe, D. L. (2017). Computer models solving intelligence test problems: progress and implications. In C. Sierra (Ed.), Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) (pp. 5005-5009). California USA: International Joint Conferences on Artificial Intelligence.
    Hernández-Orallo, José ; Martínez-Plumed, Fernando ; Schmid, Ute ; Siebers, Michael ; Dowe, David L. / Computer models solving intelligence test problems : progress and implications. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). editor / Carles Sierra. California USA : International Joint Conferences on Artificial Intelligence, 2017. pp. 5005-5009
    @inproceedings{30870e05c9e644d7939a90bd607c1eee,
    title = "Computer models solving intelligence test problems: progress and implications",
    abstract = "While some computational models of intelligence test problems were proposed throughout the second half of the XXth century, in the first years of the XXIst century we have seen an increasing number of computer systems being able to score well on particular intelligence test tasks. However, despite this increasing trend there has been no general account of all these works in terms of how they relate to each other and what their real achievements are. In this paper, we provide some insight on these issues by giving a comprehensive account of about thirty computer models, from the 1960s to nowadays, and their relationships, focussing on the range of intelligence test tasks they address, the purpose of the models, how general or specialised these models are, the AI techniques they use in each case, their comparison with human performance, and their evaluation of item difficulty.",
    author = "Jos{\'e} Hern{\'a}ndez-Orallo and Fernando Mart{\'i}nez-Plumed and Ute Schmid and Michael Siebers and Dowe, {David L.}",
    year = "2017",
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    Hernández-Orallo, J, Martínez-Plumed, F, Schmid, U, Siebers, M & Dowe, DL 2017, Computer models solving intelligence test problems: progress and implications. in C Sierra (ed.), Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). International Joint Conferences on Artificial Intelligence, California USA, pp. 5005-5009, International Joint Conference on Artificial Intelligence 2017, Melbourne, Australia, 19/08/17.

    Computer models solving intelligence test problems : progress and implications. / Hernández-Orallo, José; Martínez-Plumed, Fernando; Schmid, Ute; Siebers, Michael; Dowe, David L.

    Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). ed. / Carles Sierra. California USA : International Joint Conferences on Artificial Intelligence, 2017. p. 5005-5009.

    Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

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    T1 - Computer models solving intelligence test problems

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    AB - While some computational models of intelligence test problems were proposed throughout the second half of the XXth century, in the first years of the XXIst century we have seen an increasing number of computer systems being able to score well on particular intelligence test tasks. However, despite this increasing trend there has been no general account of all these works in terms of how they relate to each other and what their real achievements are. In this paper, we provide some insight on these issues by giving a comprehensive account of about thirty computer models, from the 1960s to nowadays, and their relationships, focussing on the range of intelligence test tasks they address, the purpose of the models, how general or specialised these models are, the AI techniques they use in each case, their comparison with human performance, and their evaluation of item difficulty.

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    Hernández-Orallo J, Martínez-Plumed F, Schmid U, Siebers M, Dowe DL. Computer models solving intelligence test problems: progress and implications. In Sierra C, editor, Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). California USA: International Joint Conferences on Artificial Intelligence. 2017. p. 5005-5009