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.
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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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