A choice prediction competition, for choices from experience and from description
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: A choice prediction competition, for choices from experience and from description
A choice prediction competition, for choices from experience and from description
1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionionEyal Ert and Alvin E. Roth - Harvard UniversityEman Haruvy - University of Texas at DallasStefan Herzog, Robin Hau, and Ralph Hertwig -- University of BaselTerrence Stewart -- University of Waterloo, Robert West -- Carleton University, andChristian Lebiere - Carnegie Mellon University40057Abstrac A choice prediction competition, for choices from experience and from descriptiont: Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: one shot decisions from description (deciA choice prediction competition, for choices from experience and from description
sions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionecision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the seco A choice prediction competition, for choices from experience and from descriptionnd (competition) set of experimental sessions. Fourteen teams responded to the challenge: the last seven authors of this paper are members of the winnA choice prediction competition, for choices from experience and from description
ing teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictio1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptioneases with the distance between the cumulative payoff functions. The best predictions of decisions from experience were obtained with models that assume reliance on small samples. Merits and limitations of the competition method are discussed.Keywords: Fitting: generalization criteria: prospect theo A choice prediction competition, for choices from experience and from descriptionry: reinforcement learning; explorative sampler, equivalent number of observations (ENO), ACT-R, the 1-800 critique.Correspondence to: Ido Erev, Max WA choice prediction competition, for choices from experience and from description
ertheimer Minerva Center for Cognitive Studies, Faculty of Industrial Engineering and Management, Technion, Haifa 32000, Israel. E-mail: erev@tx, tech1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionrch was conducted when Ido Erev was a Marvin Bower Fellow at the Harvard Business School. Ralph Hertwigand Robin Hau were supported by Swiss National Science Foundation Grant 100014-118283.Competition website: http://tx.technion.ac.il/~erev/Comp/Comp.html.2A major focus of mainstream behavioral deci A choice prediction competition, for choices from experience and from descriptionsion research has been on finding and studying counter-examples to rational decision theory, and specifically examples in which expected utility theorA choice prediction competition, for choices from experience and from description
y' can be shown to make a false prediction. This has led to a concentration of attention on situations in which utility theory' makes a clear, falsifi1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionsubjects’ beliefs. Alternative theories, such as prospect theory (Kahneman & Tversky, 1979), have been formulated to explain and generalize the deviations from utility theory observed in this way.The focus on counterexamples and their explanations has many attractive features. It has led to importan A choice prediction competition, for choices from experience and from descriptiont observations, and theoretical insights. Nevertheless, behavioral decision research may benefit from broadening this focus. The main goal of the currA choice prediction competition, for choices from experience and from description
ent research is to facilitate and explore one such direction: The study of quantitative predictions. We share a certain hesitation about proceeding to1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionterest comes in pan from the observation that the quest for accurate quantitative predictions can often be an inspiration for precise theory'. Indeed, it appears that many important scientific discoveries were triggered by an initial documentation of quantitative regularities that allow useful predi A choice prediction competition, for choices from experience and from descriptionctions.1A second motivation for the present study comes from the “1-800 critique” of behavioral research. According to this critique, the descriptionA choice prediction competition, for choices from experience and from description
of many popular models, and of the conditions under which they are expected to apply, is not clear. Thus, the authors who publish these models should 1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionlem is clarified by a comparison of exams used to evaluate college students in1 One of the earlier examples is the Pythagorean theorem. Archeological evidence suggests that the underlying regularity (the useful quantitative predictions) were known and used in Babylon 1300 years before Pythagoras (Ne A choice prediction competition, for choices from experience and from descriptionugebauer & Sachs. 1945). Pythagoras' main contribution was the clarification of the theoretical explanation of this title and its implications. AnotheA choice prediction competition, for choices from experience and from description
r important example is provided by Kepler's laws. As suggested by Klahr and Simon (1999) it seems that these laws were discovered based on data mining1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionne of the earliest and most important discoveries In Psycholog)'. Weber's law was discovered before Fechner provided an elegant theoretical explanation of this quantitative regularity. These successes of research that starts with a focus on quantitative regularities suggest that a similar approach c A choice prediction competition, for choices from experience and from descriptionan be useful in behavioral decision research too.3the exact and behavioral sciences. Typical questions in the exact sciences ask the examinees to predA choice prediction competition, for choices from experience and from description
ict the outcome OÍ a particular experiment, while typical questions in the behavioral sciences ask the examinees to exhibit understanding OÍ a particu1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptiondels of human behavior do not lead to clear predictions. A more careful study of quantitative predictions may help change tills situation.A third motivating observation conics from die discovery of important boundaries of the behavioral tendencies that best explain famous counterexamples. For exampl A choice prediction competition, for choices from experience and from descriptione, one of the most important contributions of prospec t theory (Kahneman Si Tversky, 1979) is the demonstration that two of the best-known counterexamA choice prediction competition, for choices from experience and from description
ples to expected utility theory, the Allais paradox (Allais, 1953) and the observation that people buy lotteries but also insurance (Friedman & Savage1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionrom experience demonstrate that in many settings people exhibit the opposite bias: They behave as if they underweight rare events (see Barron & Erev, 2003; Hertwig, Barron, Weber, & Erev, 2004; Hau, Pleskac, Kiefer, & Henwig, 2008; Erev, Glozman, & Hertwig, 2008: Rakow; Demes, & Newell, 2008; Ungema A choice prediction competition, for choices from experience and from descriptionch, Chater & Slewart, 2009). A focus on quantitative predictions may help identify the boundaries of the different tendencies.Finally, moving away froA choice prediction competition, for choices from experience and from description
m a focus on choices that provide counterexamples to expected utility theory' invites the study of situations in which expected utility theory may not1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from description is that, w hen participants are iree to lorm lheir own beliefs based on I heir experience, almost any decisions can be consistent with utility theory under certain assumptions concerning these beliefs.The present competition (which is of course a collaboration among many researchers) is designed in A choice prediction competition, for choices from experience and from description part to address the fact that evaluating quantitative predictions offers individual researchers different incentives than those for finding counterexA choice prediction competition, for choices from experience and from description
amples to expected utility theory. The best presentations of counterexamples typically start with the presentation of a few interesting phenomena, and1Forthcoming, Journal of Behavioral Decision Making.A choice prediction competition, for choices from experience and from descriptionIdo Erev - Techni A choice prediction competition, for choices from experience and from descriptionds to focus on many examples of a choice task. The researcher then has to estimate models, and run another large (random sample) study to compare the different models. In addition, readers of papers on quantitative prediction might be worried that the probability a particular paper will be written i A choice prediction competition, for choices from experience and from descriptionncreases if it supports the model proposed by the authors.To address this problematic incentive structure, the current research uses a choice predictiA choice prediction competition, for choices from experience and from description
on competition that can reduce the cost per investigator, and can increase the probability of insightful outcomes. The first three authors of the papeGọi ngay
Chat zalo
Facebook