This course is devoted to computational aspects of decision making in the context of data being provided by strategic agents.
The main topics that will be covered:
* Noncooperative games:
1. strategies
2. Nash equilibria
3. computational complexity (class PPAD)
* Cooperative games:
1. coalition forming
2. solution concepts
* Decision mechanisms:
1. with money (e.g. auctions)
2. without money (e.g. elections)
* Fair division
* Cost sharing mechanisms
* "price of anarchy" in the context of transportation networks
The course contains elements of computational complexity, probability theory, and convex optimization. Some prior experience with these fields would be of help, but is not formally required.
A large part of the course will follow the book:
Nisan, Routhgardan, Tardos, Vazirani. Algorithmic game theory.
https://www.cs.cmu.edu/~sandholm/cs15-892F13/algorithmic-game-theory.pdf
Another relevant book is:
Tim Roughgarden. Twenty Lectures on Algorithmic Game Theory.
https://doi.org/10.1017/CBO9781316779309
and it is based on (available) lecture notes:
https://timroughgarden.org/f13/f13.pdf
For TU Games we will use Chapter 9 from this book:
https://nibmehub.com/opac-service/pdf/read/Game%20Theory-%202nd%20edition-%202015.pdf
