Optimal stopping with behaviorally biased agents: The role of loss aversion and changing reference points
成果类型:
Article
署名作者:
Kleinberg, Jon; Kleinberg, Robert; Oren, Sigal
署名单位:
Cornell University; Ben-Gurion University of the Negev
刊物名称:
GAMES AND ECONOMIC BEHAVIOR
ISSN/ISSBN:
0899-8256
DOI:
10.1016/j.geb.2022.03.007
发表日期:
2022
页码:
282-299
关键词:
Prophet inequality
Cognitive bias
Algorithmic game theory
摘要:
We explore the implications of two central human biases studied in behavioral economics, reference points and loss aversion, in optimal stopping problems. In such problems, people evaluate a sequence of options in one pass, either accepting the option and stopping the search or giving up on the option forever. Here we assume that the best option seen so far sets a reference point that shifts as the search progresses, and a biased decision-maker's utility incurs an additional penalty when they accept a later option that is below this reference point. Our results include tight bounds on the performance of a biased agent in this model relative to the best option obtainable in retrospect (a type of prophet inequality for biased agents), as well as tight bounds on the ratio between the performance of a biased agent and the performance of a rational one. (C) 2022 Elsevier Inc. All rights reserved.