Course Description


MATH 671. Game Theory and Multiagent Systems
(3 hours of lecture per week).

There are many areas of overlap between computer science and game theory. This is not however only restricted to complexity theory which has been an instrumental tool in assessing the difficulties of game theoretical problems, e.g. optimizing the social welfare. In recent years we have witnessed the research on the interplay between game theory and distributed systems. A comprehensive look at this interplay can be found in A Computer Scientist Looks at Game Theory.

The central theme of this course is the investigation of modeling and reasoning about multi-agent systems (distributed systems of agents), who may operate on the basis of incomplete information about their environment, and with bounded computational/informational resources. We will in particular be interested in reasoning about knowledge of agents who reason about the world and each other's knowledge. An agent can be a software program, a robot or a human. This type of systems show up in a surprising number of contexts from philosophy to economics to cryptography to distributed computing.

In this course we plan to study a framework for understanding and analyzing multi-agent systems that is mathematically rigorous, useful in practice and widely applicable. We shall focus on two important and related approaches: