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

    1 Citation (Scopus)


    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 PublicationMarina del Rey CA USA
    PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
    Number of pages5
    ISBN (Electronic)9780999241103
    ISBN (Print)9780999241110
    Publication statusPublished - 2017
    EventInternational Joint Conference on Artificial Intelligence 2017 - Melbourne, Australia
    Duration: 19 Aug 201725 Aug 2017
    Conference number: 26th (Proceedings)


    ConferenceInternational Joint Conference on Artificial Intelligence 2017
    Abbreviated titleIJCAI 2017
    Internet address

    Cite this