Inverse game theory: learning the nature of a game through play

Gabriel Fortunato Stocco; George Cybenko

doi:10.1117/12.924756

21 June 2012 Inverse game theory: learning the nature of a game through play

Gabriel Fortunato Stocco, George Cybenko

Proceedings Volume 8359, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI; 835905 (2012) https://doi.org/10.1117/12.924756
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Gabriel Fortunato Stocco and George Cybenko "Inverse game theory: learning the nature of a game through play", Proc. SPIE 8359, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI, 835905 (21 June 2012); https://doi.org/10.1117/12.924756

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