As learning assessment for this course, students are asked to select a problem of scientific interest in their research field and model and solve it using the game-theoretical tools learned though the course.
As a first step, students are asked to present the problem they selected, and the objective of the analysis. They are asked to identify the components of the game that is modeling the problem (i.e., players, strategies, outcomes, utilities of players) and the game-theoretical tools they will use to solve the problem. Finally, students are asked to briefly present the methodologies currently used to model and solve the problem, and the expected differences with respect to the game-theoretical solution.
The results of this first step will be presented during the last lecture (i.e., May 20th) in a 10 minutes slot, including the presentation and a discussion with the rest of the class (consider about 7+3 min). Students may support their presentation with a slideshow of at most 5 slides.
As a second step, students are asked to actually solve at least one instance of the selected problem and compare the obtained results to the ones obtained solving the problem by currently used methodologies. Students should compare the two methodologies at least for what concerns the results, the complexity and the assumption.
The results of this second step will be presented in a written report (max 5 pages) to be sent in PDF format by email to:
The written report should include:
- The presentation of the problem and of the methodologies currently used to solve it. The report should include a reference to at least a scientific paper describing a solution to the selected problem (max 1 page);
- The modeling of the problem as a game and the specification of its components;
- The solution of the game and the description of the used game-theoretical tools;
- Results for at least an instance of the selected problem and their contrast with results obtained through at least a standard methodology;
- A comparison between at least a standard methodology and the game-theoretical approach (i.e., obtained results, complexity, assumptions, etc).