Coalitional game theory 1000-2M12TGK
During the lecture we will present key models and issues considered in coalitional game theory. Topics discussed during the course will include:
- Standard model (games in characteristic function form)
- Normative solutions to coalitional games (e..g.., the Shapley Value)
- Positive solutions to coalitional games (e.g., the core)
- Coalition structure generation
- Simple games and weighted voting games
- Graph-rerstricted games and game-theorertic network centralities
- Compact representations of coalitional games
- Games with externalities (in a partition function form)
The lecture, in addition to theoretical foundations of coalitional games, will cover newest developments in this field.
Type of course
Course coordinators
Learning outcomes
Knowledge
1. He has structured knowledge of the types of coalitional games, their
solutions and related algorithmic issues.
2. He knows the major approaches to the problem of payoff division and their properties.
3. He knows the most important concise representations of coalitional
games with good computational properties.
4. He knows the basic properties of the most important coalitional
games' applications in the area of artificial intelligence, especially in
multi-agent systems and network analysis.
5. (applicable for PhD students) He knows selected articles from the coalition game literature of recent years.
Skills
1. He can determine what type of coalitional game is the best model for
a given real-life application.
2. He can formalize given properties of coalitional game.
3. He can prove the normative and/or positive properties of a given
coalitional games' solution.
4. (applicable for PhD students) He can read and critically analyze new and more complex concepts appearing in the coalition games literature of recent years.
Competencies
1. He understand the need to use his mathematical and computer science skills and knowledge in business applications.
2. He understands the limitations of his knowledge and understand the need for further education, including gaining the knowledge outside of his main domain.
3. He can precisely formulate questions that deepen his understanding of a given topic or allows him to find the missing pieces in the reasoning process.
Assessment criteria
The final grade will consist of:
- quizzes after each lecture (10%);
- midterm written exam (40%); and
- final written exam (50%).
PhD students will additionally receive a scientific article published in the field within the last few years. Knowledge of this article will be required on the exam.
Bibliography
Osborne and Rubinstein, "A Course in Game Theory", 1994.
Peleg, Sudhölter, "Introduction to the Theory of Cooperative Games", 2003.
Chalkiadakis, Elkind and Wooldridge, "Computational Aspects of Cooperative Game Theory", 2012.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: