Game theory

Learning Results

Game Theory is the mathematical modeling of strategic interaction situations. In an interaction between two parties, everyone thinks about the situation in which they find themselves, in order to decide in the future how they should act in their interest. Game Theory, founded in 1944 by John von Neumann (creator of the corresponding computer architecture) and Oscar Morgenstern, applies to all areas of interaction, such as Computer Science, Economics, Law, Biology, Psychology and Political Philosophy.

The Game Theory course covers the basic principles of Game Theory and Mechanism Design. It aims at understanding the games, their construction, examining the different solution approaches towards answering certain questions regarding interactions, and applying Game Theory in different branches of Informatics (Information and Communication Systems Security, Networks, Cloud Computing, etc.).

Upon successful completion of the course, the student:

Will know the games that model interaction situations,

Will be able to create games by defining players, preferences, actions and payoffs,

Will know, depending on the game, how to solve it and will solve it either directly or using a tool.

Will be able to design a game in reverse (mechanism design), determining how two parts should interact under specific rules and regulations.

Will be able to use Game Theory tools where needed in his research.

Will have further developed his mathematical and algorithmic thinking.

Skills acquired

• Examine, retrieve, analyze and synthesize data and information by utilizing necessary technologies
• Decision-Making
• Work independently / Teamwork
• Project planning and management
• Work in an interdisciplinary environment
• Production of new research ideas
• Promoting free, creative and inductive thinking

The course includes the topics described in the following list:

• Introduction to Game Theory, games and solutions, Game Theory and Mechanism Design. Network applications.
• Game Theory and Computer Science, Algorithmic Game Theory, Applications.
• Strategic games, application of dominance criterion, existence and location of Nash Equilibrium, NE uniqueness in mixed strategies and behavioral strategies.
• Bayesian type games, calculation of NE in board games.
• Repetitive games, grim strategies, Folk Theorem, games with imperfect information games (imperfect information games).
• Incomplete information games, study of mixed strategies and behavioral strategies. Bayesian Nash equilibrium.
• Signaling Games.
• Mechanism Design, application at the operating system level for the implementation of security policy.
• Applications: Games on Computer Networks, Games on Information and Communication Systems Security, Games on Cloud Computing.

1. Dixit, A. and Skeath, S., Games of Strategy, 2nd edition, W.W. Norton and Company, 2004.

2. Gintis, H., Game Theory Evolving – A Problem-Centered Introduction to Modeling Strategic Interaction, Princeton University Press, 2000.

3. Kreps, D., Game Theory and Economic Modelling, Oxford University Press, 1990.

4. Osborne, M., Rubinstein, A., A Course in Game Theory, The MIT Press, 1994.

5. Noam, N., Rough garden, T., Tardos, E., Vazirani, V., Algorithmic Game Theory, Cambridge University Press, 2007.

6. Binmore, K., Playing for Real – A Text on Game Theory, Oxford University Press, 2007.

7. Leyton-Brown K., Shoham Yoav, Essentials of Game Theory: A concise, Multidisciplinary Introduction, 2008.

8. Osborne M., An Introduction to Game Theory, Oxford University Press, 2004.

Related scientific journals:

1. International Journal of Game Theory, Springer
2. Games and Economic Behavior, Elsevier

Internet sources:

1. Giacomo Bonanno , Game Theory, 2018, http://faculty.econ.ucdavis.edu/faculty/bonanno/GT_Book.html.
2. Jackson, Matthew O., A Brief Introduction to the Basics of Game Theory (December 5, 2011). Available at SSRN: https://ssrn.com/abstract=1968579 or http://dx.doi.org/10.2139/ssrn.1968579
3. Kevin Leyton-Brown and Yoav Shoham, Essentials of Game Theory (E-Book Only), A Concise Multidisciplinary Introduction, ISBN: 9781598295931 | PDF ISBN: 9781598295948, 2008, DOI: 10.2200/S00108ED1V01Y200802AIM003.