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master degree course in COMPUTER SCIENCE

Course year 1
Teaching units Unit Teoria dei Giochi: Strategie e Algoritmi
Related or Additional Studies (lesson)
  • TAF: Supplementary compulsory subjects SSD: INF/01 CFU: 6
Teachers: Matteo CAVALIERE
Moodle portal
Exam type oral
Evaluation final vote
Teaching language Italiano
Contents download pdf download




The student should acquire the fundamental concepts of game theory (strategic interactions between agents and equilibria) and apply these notions to analyze complex situations in various scenarios (social, technological). Additionally, the course aims to develop problem-solving skills and the ability to make informed decisions based on game theory. By the end of the course, the student should be able to use these skills and the appropriate analytical/computational tools to analyze and make decisions in real-world contexts, employing the principles governing strategic interactions.

Admission requirements

None. Knowledge of a programming language and basic calculus concepts can be helpful.

Course contents

(i) The concept of strategic games. Notions of strategy, payoff, rationality, and equilibrium. Introduction to game trees (definition and construction). Game solutions using the game tree structure. Examples of games with multiple players and varying complexity.
(ii) Notions of simultaneous move games with discrete strategies. Nash equilibrium, dominant strategies. Analysis of best response. Study of algorithms to find Nash equilibrium. Introduction to mixed strategies. Notions of uncertainty and information.
(iii) Repeated games, collective action games, and the prisoner's dilemma. Evolutionary game theory (EGT). The use of agent-based models to study EGT. Applications to social, economic, and technological systems.

Teaching methods

Lectures and exercises based on the application of theory to real-world problems. Attendance is not mandatory but strongly recommended. The teaching is in the Italian language, but some materials (books, slides, handouts) may be in English. Course materials will be available on Moodle. Working students who cannot regularly attend classes should inform the instructor to define specific support activities.

Assessment methods

The exam consists of a practical part and an oral part. The practical part involves the completion of a project related to modeling and solving a problem using game theory. This part of the exam assesses knowledge and understanding of game theory and the ability to apply acquired knowledge and understanding. The oral part covers topics discussed during the course and is based on an oral interview to evaluate the student's learning ability and judgment independence. The final grade is calculated as the arithmetic average of the results obtained in both parts.

Learning outcomes

Knowledge and Understanding

At the end of the course, the student will have acquired knowledge of both the theoretical and practical aspects of game theory (strategic interaction and equilibrium) and will be able to understand the specificities of various scenarios in which game theory is used in the real world

Application of Knowledge and Understanding

The student will develop skills in both analytical and computational methodologies to appropriately apply game theory techniques in modeling and solving real-world problems, with a particular emphasis on applications in complex systems of various types, such as social, economic, and technological systems.

Autonomy of Judgment

Thanks to the variety of examples considered, the student will be able to identify the most effective approaches for different cases and recognize their limitations.

Communication Skills

The student will acquire the language of game theory and the underlying "strategic" thinking and will demonstrate them during the oral part of the exam.

Learning Ability

Various cases will be examined, moving from a phenomenological description to mathematical modeling and the corresponding tools of game theory analysis. This experience will enhance the student's ability to learn new cases and tools. Furthermore, it will develop the ability to model real-world problems using a critical and interdisciplinary approach based on game theory, enabling the selection of the most appropriate approach to solve the problem at hand.


Test suggeriti

A.Dixit ed altri. Games of Strategy. WW Norton & Company, Fifth Edition

J. Watson ed altri. Strategy – An Introduction to Game Theory. WW Norton & Company, Third Edition

M.A.Nowak. Evolutionary Dynamics – Exploring the Equation of Life. Harvard University Press, 2006.