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| Content Provider | ACM Digital Library |
|---|---|
| Author | Lucier, Brendan Immorlica, Nicole Gravin, Nick Pountourakis, Emmanouil |
| Abstract | Individuals working towards a goal often exhibit time inconsistent behavior, making plans and then failing to follow through. One well-known model of such behavioral anomalies is present-bias discounting: individuals over-weight present costs by a bias factor. This model explains many time-inconsistent behaviors, but can make stark predictions in many settings: individuals either follow the most efficient plan for reaching their goal or procrastinate indefinitely. We propose a modification in which the present-bias parameter can vary over time, drawn independently each step from a fixed distribution. Following Kleinberg and Oren (2014), we use a weighted {\it task graph} to model task planning, and measure the cost of procrastination as the relative expected cost of the chosen path versus the optimal path. We use a novel connection to optimal pricing theory to describe the structure of the worst-case task graph for any present-bias distribution. We then leverage this structure to derive conditions on the bias distribution under which the worst-case ratio is exponential (in time) or constant. We also examine conditions on the task graph that lead to improved procrastination ratios: graphs with a uniformly bounded distance to the goal, and graphs in which the distance to the goal monotonically decreases on any path. |
| Starting Page | 361 |
| Ending Page | 361 |
| Page Count | 1 |
| File Format | |
| ISBN | 9781450339360 |
| DOI | 10.1145/2940716.2940774 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-07-21 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Procrastination Graph theory Behavioral economics |
| Content Type | Text |
| Resource Type | Article |
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