@inproceedings{6d66249ab8474a00805815231e950350,
title = "A computational model for decision tree search",
abstract = "How do people plan ahead in sequential decision-making tasks? In this article, we compare computational models of human behavior in a challenging variant of tic-tac-toe, to investigate the cognitive processes underlying sequential planning. We validate the most successful model by predicting choices during games, two-alternative forced choices and board evaluations. We then use this model to study individual skill differences, the effects of time pressure and the nature of expertise. Our findings suggest that people perform less tree search under time pressure, and that players search more as they improve during learning.",
keywords = "Behavioral modeling, Expertise, Sequential decision-making",
author = "{van Opheusden}, Bas and Gianni Galbiati and Zahy Bnaya and Yunqi Li and Ma, {Wei Ji}",
note = "Funding Information: This work was supported by grant IIS-1344256 from the National Science Foundation Publisher Copyright: {\textcopyright} CogSci 2017.; 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 ; Conference date: 26-07-2017 Through 29-07-2017",
year = "2017",
language = "English (US)",
series = "CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition",
publisher = "The Cognitive Science Society",
pages = "1254--1259",
booktitle = "CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society",
}