Algorithmic Game Theory
Algorithmic Game Theory
Course with SWS 2/2/0 (lecture/exercise/practical) in SS 2023
Lecturer
Tutor
SWS
- 2/2/0
Modules
Examination method
- Written exam
- Oral exam
Game Theory is a multi-disciplinary and pervasive field that is concerned with how strategic decision making can be formally modelled and analysed.
In this course, we will approach the subject from a computer science perspective and also address how game theory can be approached computationally, e.g. consider how computers can be programmed to play games, or analyse the computational complexity of various game-theoretic notions.
Dates and times
The lecture takes place in a hybrid fashion on Mondays, DS3, in APB E005 (where seats will be available on a first-come, first-serve basis) and via Zoom. Similarly, the exercise sessions take place on Mondays, DS6, in APB E005, and can be accessed virtually via BigBlueButton. The online-whiteboard used during the exercise sessions can be accessed via Miro. Keep in mind that the notes on the whiteboard are not necessarily complete and do not serve as sample solutions.
Topics
- Noncooperative games in normal form
- Noncooperative games in extensive form
- Search in game trees
- Games with missing information
- Evolutionary game theory
- General Game Playing
- Cooperative Games
- Jörg Rothe (Ed.): Economics and Computation. An Introduction to Algorithmic Game Theory, Computational Social Choice, and Fair Division. Springer-Verlag Berlin Heidelberg (2016) (Part I: Playing Successfully)
- Lectures 1, 2, 6, and 7
- Richard Alan Gillman, David Housman: Game Theory. A Modeling Approach. CRC Press (2019)
- Lectures 1, 2, 3, and 8
- Stuart J. Russell, Peter Norvig: Artificial Intelligence. A Modern Approach (Global Edition). Pearson (2021) (Chapter 6: Adversarial Search and Games)
- Lectures 4 and 5
- Noam Nisan, Tim Roughgarden, Éva Tardos, Vijay Vazirani (eds.): Algorithmic Game Theory. Cambridge University Press (2007)
- Lecture 8
- Michael R. Genesereth, Michael Thielscher: General Game Playing (Synthesis Lectures on Artificial Intelligence and Machine Learning) Morgan & Claypool Publishers (2014)
- Lectures 4, 5, and 9
- Bernhard von Stengel: Game Theory Basics. Cambridge University Press (2021)
Subscribe to events of this course (icalendar)
| No session | Room occupied by RoboLab | DS3, April 3, 2023 in APB E005 | |
| No session | Public holiday | DS3, April 10, 2023 in APB E005 | |
| Lecture | Noncooperative Games in Normal Form | DS3, April 17, 2023 in Video conference | File |
| Lecture | Normal-Form Games: Mixed Strategies | DS3, April 24, 2023 in Video conference | File |
| Exercise | Noncooperative Games in Normal Form | DS6, April 24, 2023 in Video conference | File |
| No session | Public holiday | DS3, May 1, 2023 in APB E005 | |
| Lecture | Sequential Games with Perfect Information | DS3, May 8, 2023 in Video conference | File |
| Exercise | Normal-Form Games: Mixed Strategies | DS6, May 8, 2023 in Video conference | File |
| Lecture | Playing Games: Alpha-Beta Tree Search | DS3, May 15, 2023 in Video conference | File |
| Exercise | Sequential Games with Perfect Information | DS6, May 15, 2023 in Video conference | File |
| Lecture | Playing Games: Monte Carlo Tree Search | DS3, May 22, 2023 in Video conference | File |
| Exercise | Playing Games: Alpha-Beta Tree Search | DS6, May 22, 2023 in Video conference | File |
| No session | Public holiday | DS3, May 29, 2023 in APB E005 | |
| Lecture | Games with Missing Information: Modelling | DS3, June 5, 2023 in Video conference | |
| Exercise | Playing Games: Monte Carlo Tree Search | DS6, June 5, 2023 in APB E005 | File |
Calendar
