Description:
The course aims at introducing the main paradigms of game theory within an algorithmic perspective in order to analyse the behaviour of multi-agent systems and phenomena.
Suitable mathematical models and tools will be provided to help the understanding of inner mechanisms of competition and cooperation, threads and promises. A critical analysis of the power and limitations of game theory is addressed as well together with a few applications to problems from different areas (such as economics, computer science, engineering).

Knowledge:
The course provides the main theoretical concepts of cooperative and noncooperative games together with the main algorithms for their analysis. The theoretical analysis will be paired with applications to problems from a wide range of different areas. Applications will be chosen upon the students’ interests (e.g., ranging from computational economics and social sciences to traffic, ITC and social networks, energy management, blockchain technologies, security, pattern recognition and machine learning).


Skills:
The course aims at providing student suitable background to
• formulate and analyse phenomena and systems with interactions between multiple agents/decision-makers
• understand inner mechanisms of competition and cooperation
• understand inner mechanisms of threads and promises
• forecast the behaviour of agents
• design mechanisms to steer systems towards desired objectives through adequate mathematical models.

Syllabus:
• Noncooperative games
• Auctions and bargaining
• Cooperative games
• Game theory in practice
• Applications (computer science, economic computation et al.)