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Correction published on 21 July 2010, see Games 2010, 1(3), 221-225.
Article

A Choice Prediction Competition for Market Entry Games: An Introduction

by 1,*, 2 and 3,4
1
Max Wertheimer Minerva Center for Cognitive Studies, Faculty of Industrial Engineering and Management, Technion, Haifa 32000, Israel
2
Computer Laboratory for Experimental Research, Harvard Business School, Boston, MA, 02163, USA
3
Department of Economics, 308 Littauer, Harvard University, Cambridge, MA 02138, USA
4
Harvard Business School, 441 Baker Library, Boston, MA 02163, USA
*
Author to whom correspondence should be addressed.
Games 2010, 1(2), 117-136; https://doi.org/10.3390/g1020117
Received: 30 April 2010 / Accepted: 12 May 2010 / Published: 14 May 2010
(This article belongs to the Special Issue Predicting Behavior in Games)
A choice prediction competition is organized that focuses on decisions from experience in market entry games (http://sites.google.com/site/gpredcomp/ and https://www.mdpi.com/si/games/predict-behavior/). The competition is based on two experiments: An estimation experiment, and a competition experiment. The two experiments use the same methods and subject pool, and examine games randomly selected from the same distribution. The current introductory paper presents the results of the estimation experiment, and clarifies the descriptive value of several baseline models. The experimental results reveal the robustness of eight behavioral tendencies that were documented in previous studies of market entry games and individual decisions from experience. The best baseline model (I-SAW) assumes reliance on small samples of experiences, and strong inertia when the recent results are not surprising. The competition experiment will be run in May 2010 (after the completion of this introduction), but they will not be revealed until September. To participate in the competition, researchers are asked to E-mail the organizers models (implemented in computer programs) that read the incentive structure as input, and derive the predicted behavior as an output. The submitted models will be ranked based on their prediction error. The winners of the competition will be invited to publish a paper that describes their model. View Full-Text
Keywords: reinforcement learning; excess entry; recency; surprise triggers change; inertia reinforcement learning; excess entry; recency; surprise triggers change; inertia
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MDPI and ACS Style

Erev, I.; Ert, E.; Roth, A.E. A Choice Prediction Competition for Market Entry Games: An Introduction. Games 2010, 1, 117-136. https://doi.org/10.3390/g1020117

AMA Style

Erev I, Ert E, Roth AE. A Choice Prediction Competition for Market Entry Games: An Introduction. Games. 2010; 1(2):117-136. https://doi.org/10.3390/g1020117

Chicago/Turabian Style

Erev, Ido, Eyal Ert, and Alvin E. Roth 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction" Games 1, no. 2: 117-136. https://doi.org/10.3390/g1020117

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