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Proceedings Paper

Inverse game theory: learning the nature of a game through play
Author(s): Gabriel Fortunato Stocco; George Cybenko
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Paper Abstract

Real world adversarial dynamics such as those encountered in Computer and Network security require models which allow for both imperfect and incomplete information. Recently game theoretic models and specically signaling games have been at the forefront of interest for modeling these scenarios. We propose a modication of signaling games, a type of Bayesian game, which we believe can serve as a model for these scenarios. By incorporating real world data into the model, these games could allow interested parties to learn the true nature of the game that they are already playing - though without the rulebook.

Paper Details

Date Published: 21 June 2012
PDF: 10 pages
Proc. SPIE 8359, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI, 835905 (21 June 2012); doi: 10.1117/12.924756
Show Author Affiliations
Gabriel Fortunato Stocco, Dartmouth College (United States)
George Cybenko, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 8359:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI
Edward M. Carapezza, Editor(s)

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