Heuristic Search of Heuristics

Angelo Pirrone, Peter Lane, Laura Bartlett, Noman Javed, Fernand Gobet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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How can we infer the strategies that human participants adopt to carry out a task? One possibility, which we present and discuss here, is to develop a large number of strategies that participants could have adopted, given a cognitive architecture and a set of possible operations. Subsequently, the (often many) strategies that best explain a dataset of interest are highlighted. To generate and select candidate strategies, we use genetic programming, a heuristic search method inspired by evolutionary principles. Specifically, combinations of cognitive operators are evolved and their performance compared against human participants’ performance on a specific task. We apply this methodology to a typical decision-making task, in which human participants were asked to select the brighter of two stimuli. We discover several understandable, psychologically-plausible strategies that offer explanations of participants’ performance. The strengths, applications and challenges of this methodology are discussed.
Original languageEnglish
Title of host publicationArtificial Intelligence XL
Subtitle of host publication43rd SGAI International Conference on Artificial Intelligence, AI 2023, Proceedings
EditorsM Bramer, F Stahl
PublisherSpringer Nature
Number of pages14
ISBN (Electronic)978-3-031-47994-6
ISBN (Print)978-3-031-47993-9
Publication statusE-pub ahead of print - 8 Nov 2023
EventInternational Conference on Innovative Techniques and Applications of Artificial Intelligence - Cambridge, United Kingdom
Duration: 12 Dec 202314 Dec 2023

Publication series

NameLecture Notes in Computer Science book series
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Innovative Techniques and Applications of Artificial Intelligence
Country/TerritoryUnited Kingdom
Internet address


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