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Predict choice: A comparison of 21 mathematical models

Schulz, E; Speekenbrink, M; Shanks, DR; (2014) Predict choice: A comparison of 21 mathematical models. In: Bello, P and Gaurini, M and McShane, M and Scassellati, B, (eds.) Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pp. 2889 - 2894). Cognitive Science Society: Austin, TX. Green open access

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Abstract

How should we choose a model that predicts human choices? Two important factors in this choice are a model's predictive power and a model's fexibility. In this paper, we compare these aspects of models in a large set of models applied to an experiment in which participants chose between brands of fictitious chocolate bars and a quasi-experiment predicting movies' gross revenue. We show that there is a trade-o ff between flexibility and predictive power, but that this trade-o ff appears to lie more towards the "flexible" side than what was previously thought.

Type: Proceedings paper
Title: Predict choice: A comparison of 21 mathematical models
ISBN-13: 978-0-9911967-0-8
Open access status: An open access version is available from UCL Discovery
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/1437390
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