Game Theory is centred around mathematical models of conflict and cooperation. It plays an increasingly important role in many branches of science, such as Economics, Biology, Computer Science, Psychology, Political Science, Law and Medicine. The societal relevance of Game Theory is also illustrated by the fact that quite a few game theorists have been awarded the Nobel Prize in Economics, like 'beautiful mind’ John Nash in 1994. Nearly everyone has heard of the Prisoners' Dilemma, but what is really the issue? In these lectures, we introduce the basic concepts and examine several branches of this exciting field.

The individual lectures
1. Introduction to Game Theory (Thuijsman / 1 Nov)
We discuss the main concepts introduced by some of the founding fathers of Game Theory and part of their impact in modern day life. This will include strategic (or non-cooperative) models, where players want to optimize their individual utilities w.r.t. what others are doing, axiomatic approaches to fair ways of sharing profits or losses in non-strategic (or cooperative) models, and evolutionary models that are governed by a Darwinian way of fitness maximization.

2. Social Choice (Peters / 8 Nov)
The theory of social choice is concerned with aggregating individual preferences into a collective preference. Both normative aspects and strategic considerations come into play. In this lecture we discuss theoretical  insights as well as consequences for practical applications, such as political elections.

3. Experimental, Behavioral and Neuronal Game (Riedl / 15 Nov)
Casual observations suggest and economic experiments have shown that 'human players' often behave differently from 'game theory players'. In contrast to the latter, the former take into account others well-being, my feel guilt and anger, and have less cognitive calculation power. In this lecture we will discuss empirical regularities of human behavior in games, will have a first glimpse into the neurobiological basis of such behavior, and how behavioral game theory attempts to account for the deviations from 'standard' game theoretical predictions.

4. Algorithmic Game Theory (Mihalak / 22 Nov)
Algorithmic game theory lies at the intersection of game theory and computer science, addressing (1) computational issues in game theory such as "Can an equilibrium be computed efficiently (in reasonable time)?", or "Can we design a game where the outcome can be computed efficiently?", and addressing (2) strategic-behavior in the computer science domain, such as "What is the congestion on road networks when drivers choose their routes selfishly?", or "Is the Internet an equilibrium of a game? If yes, of what game?". In this lecture, we will touch upon some of these questions, and provide a gentle introduction to the field.