@inproceedings{937285c3d81e468a8b9f38cdc77a4c46,
title = "Principal-Agent Problems with Present-Biased Agents",
abstract = "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{\textquoteright}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{\textquoteright}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.",
author = "Sigal Oren and Dolav Soker",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Symposium on Algorithmic Game Theory, SAGT 2019 ; Conference date: 30-09-2019 Through 03-10-2019",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-30473-7_16",
language = "American English",
isbn = "9783030304720",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "237--251",
editor = "Dimitris Fotakis and Evangelos Markakis",
booktitle = "Algorithmic Game Theory - 12th International Symposium, SAGT 2019, Proceedings",
address = "Germany",
}