Chapter The Price of Uncertainty in Present-Biased Planning (Record no. 43686)

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000 -LEADER
fixed length control field 03053naaaa2200517uu 4500
001 - CONTROL NUMBER
control field https://directory.doabooks.org/handle/20.500.12854/31947
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 978-3-319-71924-5_23
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-319-71924-5_23
Terms of availability doi
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title English
042 ## - AUTHENTICATION CODE
Authentication code dc
072 #7 - SUBJECT CATEGORY CODE
Subject category code U
Source bicssc
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Albers, Susanne
Relationship auth
245 10 - TITLE STATEMENT
Title Chapter The Price of Uncertainty in Present-Biased Planning
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Name of publisher, distributor, etc. Springer Nature
Date of publication, distribution, etc. 2017
300 ## - PHYSICAL DESCRIPTION
Extent 1 electronic resource (15 p.)
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open Access
Source of term star
Standardized terminology for access restriction Unrestricted online access
520 ## - SUMMARY, ETC.
Summary, etc. 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.
540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE
Terms governing use and reproduction Creative Commons
Use and reproduction rights https://creativecommons.org/licenses/by/4.0/
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-- https://creativecommons.org/licenses/by/4.0/
546 ## - LANGUAGE NOTE
Language note English
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computing & information technology
Source of heading or term bicssc
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term behavioral economics
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Uncontrolled term incentive design
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Uncontrolled term heterogeneous agents
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Uncontrolled term approximation algorithms
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Uncontrolled term variable present bias
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Uncontrolled term penalty fees
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Uncontrolled term behavioral economics
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Uncontrolled term incentive design
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Uncontrolled term heterogeneous agents
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Uncontrolled term approximation algorithms
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Uncontrolled term variable present bias
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Uncontrolled term penalty fees
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Uncontrolled term Alice and Bob
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Uncontrolled term Decision problem
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Uncontrolled term Graph theory
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Uncontrolled term Graphical model
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Uncontrolled term NP (complexity)
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Uncontrolled term Time complexity
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Uncontrolled term Upper and lower bounds
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kraft, Dennis
Relationship auth
773 10 - HOST ITEM ENTRY
Host Biblionumber OAPEN Library ID: 644832
Control subfield nnaa
856 40 - ELECTRONIC LOCATION AND ACCESS
Host name www.oapen.org
Uniform Resource Identifier <a href="https://library.oapen.org/bitstream/20.500.12657/30615/1/644832.pdf">https://library.oapen.org/bitstream/20.500.12657/30615/1/644832.pdf</a>
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Public note DOAB: download the publication
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Host name www.oapen.org
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Public note DOAB: download the publication
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Uniform Resource Identifier <a href="https://directory.doabooks.org/handle/20.500.12854/31947">https://directory.doabooks.org/handle/20.500.12854/31947</a>
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