Computer Models Solving Intelligence Test Problems: Progress and Implications (Extended Abstract)

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

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, despitethis increasing trend there has been no general account of all these works in terms of how theyrelate to each other and what their real achievements are. In this paper, we provide some insighton these issues by giving a comprehensive account of about thirty computer models, from the 1960sto nowadays, and their relationships, focussing on the range of intelligence test tasks they address, thepurpose of the models, how general or specialised these models are, the AI techniques they use in eachcase, their comparison with human performance, and their evaluation of item difficulty.