Albers, Susanne <br/><br/>
Chapter The Price of Uncertainty in Present-Biased Planning 

 -  Springer Nature  2017 
 - 1 electronic resource (15 p.) 
<br/><br/> Open Access 
<br/><br/> 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’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 effi-  ciency 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. 
<br/><br/><br/>Creative Commons 
<br/><br/><br/>English 
<br/><br/><label>ISBN: </label>978-3-319-71924-5_23 
<br/><br/><label>Standard No.: </label>10.1007/978-3-319-71924-5_23  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computing & information technology
<br/><br/><label>Subjects--Index Terms: </label>behavioral economics incentive design heterogeneous agents approximation algorithms variable present bias penalty fees behavioral economics incentive design heterogeneous agents approximation algorithms variable present bias penalty fees Alice and Bob Decision problem Graph theory Graphical model NP (complexity) Time complexity Upper and lower bounds