Games, Mechanisms, Rationality & Decisions

This course treats with different aspects of and viewpoints on rationality and decision-making, trying to cover a broad range of approaches and methods ranging from techniques developed in computer sciences and mathematical economy to concepts from psychology and cognitive science.

The course is conceptually divided into two parts:

In the first block, after a general introduction to basic methods from strategic game theory and mechanism design, we will have a closer look at some advanced topics within the respective fields, also touching recent research from areas as diverse as e-commerce and auction mechanisms, computational social choice, and voting theory.

The second block will more be based on approaches from psychology and cognitive science, introducing classical theories of rationality and decision-making, but also discussing recent developments and proposals within the topic area. Whilst the first block will mainly be based on lectures and tutorials given by the lecturer, students (guided and suported by the lecturer) will give presentations on selected articles during the second half of the course.

Overview:

- Games, Mechanisms, Choice: General Overview of the Course, Introduction to Strategic Game Theory (L); Introduction to Strategic Game Theory (L); Equilibria and Solution Concepts (L/SP); Introduction to Mechanism Design (L); Advanced Mechanisms, E-Commerce and the GSP (L/SP); Introduction to Computational Social Choice (L); Voting Theory (L/SP), Fair Division (SP).

- Rationality, Heuristics, and Friends: Expected Utility Model (SP); Bounded Rationality (SP); New Expectation Theory (SP); Bayesian Rationality (SP); Logic & Rationality (SP); Gigerenzer's Heuristics (SP); Rationality & Cognitive Modeling (SP).

(L: Lecture; SP: Student Presentation)