Please use this identifier to cite or link to this item:
|Title:||A dynamic level-K model in sequential games|
|Authors:||Ho, T.-H. |
Behavioral game theory
|Source:||Ho, T.-H., Su, X. (2013). A dynamic level-K model in sequential games. Management Science 59 (2) : 452-469. ScholarBank@NUS Repository. https://doi.org/10.1287/mnsc.1120.1645|
|Abstract:||Backward induction is a widely accepted principle for predicting behavior in sequential games. In the classic example of the "centipede game," however, players frequently violate this principle. An alternative is a "dynamic level-k" model, where players choose a rule from a rule hierarchy. The rule hierarchy is iteratively defined such that the level-k rule is a best response to the level-4k.15 rule, and the level-. rule corresponds to backward induction. Players choose rules based on their best guesses of others' rules and use historical plays to improve their guesses. The model captures two systematic violations of backward induction in centipede games, limited induction and repetition unraveling. Because the dynamic level-k model always converges to backward induction over repetition, the former can be considered to be a tracing procedure for the latter. We also examine the generalizability of the dynamic level-k model by applying it to explain systematic violations of backward induction in sequential bargaining games. We show that the same model is capable of capturing these violations in two separate bargaining experiments. © 2013 INFORMS.|
|Source Title:||Management Science|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
WEB OF SCIENCETM
checked on Nov 17, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.