Principal-Agent Problems with Present-Biased Agents

Sigal Oren, Dolav Soker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


We present a novel graph-theoretic principal-agent model in which the agent is present biased (a bias that was well studied in behavioral economics). Our model captures situations in which a principal guides an agent in a complex multi-step project. We model the different steps and branches of the project as a directed acyclic graph with a source and a target, in which each edge has the cost for completing a corresponding task. If the agent reaches the target it receives some fixed reward R. We assume that the present-biased agent traverses the graph according to the framework of Kleinberg and Oren (EC’14) and as such will continue traversing the graph as long as his perceived cost is less than R. We further assume that each edge is assigned a value and if the agent reaches the target the principal’s payoff is the sum of values of the edges on the path that the agent traversed. Our goal in this work is to understand whether the principal can efficiently compute a subgraph that maximizes his payoff among all subgraphs in which the agent reaches the target. For this central question we provide both impossibility results and algorithms.

Original languageEnglish
Title of host publicationAlgorithmic Game Theory - 12th International Symposium, SAGT 2019, Proceedings
EditorsDimitris Fotakis, Evangelos Markakis
Number of pages15
ISBN (Print)9783030304720
StatePublished - 1 Jan 2019
Event12th International Symposium on Algorithmic Game Theory, SAGT 2019 - Athens, Greece
Duration: 30 Sep 20193 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11801 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Symposium on Algorithmic Game Theory, SAGT 2019


Dive into the research topics of 'Principal-Agent Problems with Present-Biased Agents'. Together they form a unique fingerprint.

Cite this