Computational Scientific Discovery in Cognitive Science

AI-guided scientific discovery will become an indispensable tool for scientists in the not too distant future. This half-day tutorial begins by introducing the area of computational scientific discovery within the cognitive sciences along with an overview of recent models of cognitive behaviour developed using these tools. The second half of the tutorial presents a detailed walk-through of our methodology and computational system, where participants will learn how to design experiments, evolve and analyse candidate models using the GEMS (Genetically Evolving Models in Science) system. Although specialised towards the cognitive sciences, many of the principles of model definition and discovery can be more broadly applied, and so the tutorial should be of interest to the wider Cognitive Machine Intelligence community.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/cogmi62246.2024.00043
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Computational Scientific Discovery in Cognitive Science

Peter C. R. Lane, Fernand R. Gobet
Neural Networks and Applications
article

Computational Scientific Discovery in Cognitive Science

Peter C. R. Lane, Fernand R. Gobet
article en

Abstract

AI-guided scientific discovery will become an indispensable tool for scientists in the not too distant future. This half-day tutorial begins by introducing the area of computational scientific discovery within the cognitive sciences along with an overview of recent models of cognitive behaviour developed using these tools. The second half of the tutorial presents a detailed walk-through of our methodology and computational system, where participants will learn how to design experiments, evolve and analyse candidate models using the GEMS (Genetically Evolving Models in Science) system. Although specialised towards the cognitive sciences, many of the principles of model definition and discovery can be more broadly applied, and so the tutorial should be of interest to the wider Cognitive Machine Intelligence community.

University of Hertfordshire (GB), London School of Economics and Political Science (GB)
European Research Council
Openalex Percentile: Top 76%
Neural Networks and Applications
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