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Time-inconsistent planning: a computational problem in behavioral economics

Published:21 February 2018Publication History
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Abstract

In many settings, people exhibit behavior that is inconsistent across time---we allocate a block of time to get work done and then procrastinate, or put effort into a project and then later fail to complete it. An active line of research in behavioral economics and related fields has developed and analyzed models for this type of time-inconsistent behavior.

Here we propose a graph-theoretic model of tasks and goals, in which dependencies among actions are represented by a directed graph, and a time-inconsistent agent constructs a path through this graph. We first show how instances of this path-finding problem on different input graphs can reconstruct a wide range of qualitative phenomena observed in the literature on time-inconsistency, including procrastination, abandonment of long-range tasks, and the benefits of reduced sets of choices. We then explore a set of analyses that quantify over the set of all graphs; among other results, we find that in any graph, there can be only polynomially many distinct forms of time-inconsistent behavior; and any graph in which a time-inconsistent agent incurs significantly more cost than an optimal agent must contain a large "procrastination" structure as a minor. Finally, we use this graph-theoretic model to explore ways in which tasks can be designed to motivate agents to reach designated goals.

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  1. Time-inconsistent planning: a computational problem in behavioral economics

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    • Published in

      cover image Communications of the ACM
      Communications of the ACM  Volume 61, Issue 3
      March 2018
      107 pages
      ISSN:0001-0782
      EISSN:1557-7317
      DOI:10.1145/3190347
      Issue’s Table of Contents

      Copyright © 2018 ACM

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      Publication History

      • Published: 21 February 2018

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