While game theory has been able to make useful predictions in many situations of interest, it is well known that, in many games of interest, the predictions of game theory are simply incorrect. This project focuses on one potential explanation: players' computational limitations. Game theory has assumed that all players are rational. In the literature, "rational" is taken to mean, among other things, that players can compute their beliefs and a best response to what they believe other players are doing. But such computations may not be so easy to perform. The project will still assume that players are rational, but will try to model explicitly the fact that people are computationally bounded and are affected by how games are framed/described in terms of language. It will then consider the consequences of assuming that people are playing rationally in the sense of doing the best that they can, subject to their computational limitations and how they describe their world.

More specifically, the project will focus on three inter-related topics. 1) Taking computation into account in human behavior: The project will investigate how the formal models introduced in the PI's earlier work on games with computationally bounded players can be used to explain human behavior such as rational inattention, where people seem to ignore variables that seem relevant, and anomalies in human behavior in real-world deployments of game theory to applications such as security of wildlife and fisheries, forest protection, and drug interdiction. 2) Computational and language issues in dynamic games: Intuitively, as an agent does computation, his understanding of the game improves, his judgments of uncertainty becomes sharper, he may become aware of more options, and his utility function may change. The project will investigate approaches to modeling this process, including issues such as procrastination effects ("I'd rather start my diet tomorrow and eat the chocolate cake today than start my diet today"; if this reasoning is applied every day, the agent will never start his diet). 3) Cryptography and game theory: Modern cryptography can usefully be viewed as a game between resource-bounded agents. The project will investigate these connections, with the hope of being able to design better cryptographic protocols. One concrete outcome of the work will be better mechanisms for achieving desired outcomes. For example, understanding the effect of computational limitations on people's behavior may enable better mechanisms for preventing poaching. A particular focus area will be Bitcoin, which can be viewed as a game between resource-bounded miners.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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James Donlon
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Cornell University
United States
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