@inproceedings{0178ee26b23a4ee9ac6a6f1e97938d49,
title = "The price of uncertainty in present-biased planning",
abstract = "The tendency to overestimate immediate utility is a common cognitive bias. As a result people behave inconsistently over time and fail to reach long-term goals. Behavioral economics tries to help affected individuals by implementing external incentives. However, designing robust incentives is often difficult due to imperfect knowledge of the parameter β∈ (0, 1 ] quantifying a person{\textquoteright}s present bias. Using the graphical model of Kleinberg and Oren [8], we approach this problem from an algorithmic perspective. Based on the assumption that the only information about β is its membership in some set B⊂ (0, 1 ], we distinguish between two models of uncertainty: one in which β is fixed and one in which it varies over time. As our main result we show that the conceptual loss of efficiency incurred by incentives in the form of penalty fees is at most 2 in the former and 1 + max B/ min B in the latter model. We also give asymptotically matching lower bounds and approximation algorithms.",
keywords = "Approximation algorithms, Behavioral economics, Heterogeneous agents, Incentive design, Penalty fees, Variable present bias",
author = "Susanne Albers and Dennis Kraft",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2017.; 13th International Conference on Web and Internet Economics, WINE 2017 ; Conference date: 17-12-2017 Through 20-12-2017",
year = "2017",
doi = "10.1007/978-3-319-71924-5_23",
language = "English",
isbn = "9783319719238",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "325--339",
editor = "Devanur, {Nikhil R.} and Pinyan Lu",
booktitle = "Web and Internet Economics - 13th International Conference, WINE 2017, Proceedings",
}