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

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.