Decision making as a shared endeavor rapidly extends game theory into many real world situations and helps us to see how these ideas can be applied to problems that impact all of us. We start with a discussion about water resources and their allocation. This then is tied back to how we think about the classic problem of the prisoner's dilemma.

For many real-world settings we are not fully cooperative and may even be playing a game with antagonistic opponents. Understanding an optimal strategy for these settings means paying attention to the moves possible from the opponent and what they mean for your own optimal actions. We start with considerations of cybersecurity and then move into the classic Centipede Game.

The game of Diplomacy is a challenge due to the many combinatorial options that can flow from a set of decisions. The game can be quite complex to play and also provides an excellent training ground for computer algorithms. In this part of the course we look at the general nature of complex social interactions and the models for game play that can be used to define optimal policies.

In this fifth module we aim to generalize from our study of games as objects in their own right to algorithms and informational settings where the ideas from game theory can inspire new insights and ways to see into large and diverse datasets. We start with a common clinical problem: how to classify a radiological image. As we think about the challenges of this setting, including extracting and seeing the relevant features, we set the frame for our goals with this fifth week. In particular, how can we find the most important, and ideally invariant, features that best describe our problem and that can be used for making decisions.