
Course unit
GAME THEORY
INP9087836, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2019/20
Mutuating
Course unit code 
Course unit name 
Teacher in charge 
Degree course code 
INP4064059 
GAME THEORY 
LEONARDO BADIA 
IN0521 
ECTS: details
Type 
ScientificDisciplinary Sector 
Credits allocated 
Core courses 
INGINF/03 
Telecommunications 
6.0 
Course unit organization
Period 
First semester 
Year 
1st Year 
Teaching method 
frontal 
Type of hours 
Credits 
Teaching hours 
Hours of Individual study 
Shifts 
Lecture 
6.0 
48 
102.0 
No turn 
Prerequisites:

A course, even a basic one, on probability theory. 
Target skills and knowledge:

The course involves the acquisition of the following elements of knowledge and proficiencies, divided in two sets.
(1: basic objectives) To learn and master basic and advanced theoretical concepts of game theory and to know how to solve general multiobjective multiagent problems with game theory techniques.
(2: applied objectives) To be able to apply game theory concepts to practical scenarios, especially in the ICT context; in particular, it is relevant to contextualize game theory as an instrument for the evaluation of the effectiveness of the solution process in distributed multiagent procedures.
According to the enrollment/frequency/mutuation of the student, the importance of these two sets is considered differently. In particular, applied objectives are achievable only by engineering students that are regularly attending the course. For students belonging to different programs and/or not regularly attending lectures, the acquisition of knowledge and skills focuses on the first set of basic objectives. 
Examination methods:

For the students of engineering programs with regular attendance to the course (differently from other kinds of students), the exam involves the development of a project in 13 person groups, on courserelated topics applied to ICT. This is agreed halfway through the course together with the lecturer.
For all the students, in any event the exam also includes a mandatory openbook written test, containing four problems of game theory focusing on different topics of the course. Every exercise involves three questions.
For engineering students with regular attendance to the course, the written test is limited to solving three exercises out of four. For the other students (nonengineering students or students without regular attendance), the written test involves all of the four exercises.
If the written test is sufficient, nonengineering students or students without regular attendance can directly finalize the passing score. Engineering students with regular attendance instead discuss their project with an oral exam after the written test. Oral exams are scheduled in the same day of written tests (even though students can decide to give the two parts on separate days). Both the written test and the oral exam must be sufficient to pass. 
Assessment criteria:

Every question in the written exam awards up to 3 points.
For engineering students with regular attendance, the project discussion awards up to 10 points.
The final mark is the numerical sum of the scores achieved in the questions and the project discussion (if present), capped to 30. Honors are awarded to students with a final numerical score higher than 31.
Every question in the written test will be evaluated according to:
 pertinence, correctness, and completeness of the answer;
 proper usage of terminology, methodology, and formal representations of game theory;
 acquired attitude towards problem solving
 attitude towards discussion and expost verification of the solution found
For the project evaluation (if present), the following aspects will be considered:
 originality of the proposal, and their pertinence with both the course topics and the engineering methodologies in ICT contexts
 quality of the oral exposition
 attitude towards teamwork and the presence of individual contributions relatable to every single participants
 attitude towards drawing meaningful conclusions from a scientific standpoint thanks to the methodologies learned during the course 
Course unit contents:

Basic concepts of game theory
Utility, market, discount factor
Static games in normal form
Dominance, Nash equilibrium
Efficiency, price of anarchy
Zerosum games, minmax games
Mixed strategies, mixed equilibria
Nash theorem, minmax theorem
The tragedy of the commons
Dynamic games
Strategy and subgames
Backward utility
Stackelberg equilibria
Repeated games and cooperation
Dynamic duopolies, collusion
Cooperation, pricing
Imperfect/incomplete information
Bayesian games, signaling, beliefs
Revelation principle
Axiomatic game theory
Fictitious play
Best response dynamics
Distributed optimization
Algorithmic game theory
Computation, complexity, and completeness of equilibria
Auctions, bargaining
Firstprice and secondprice auctions
VCG principle
Cooperative games: the core, the Shapley value
Resource allocation
Utilities, choices, and paradoxes
Potential games, coordination
Bioinspired algorithms
Evolutionary games
Cognitive networks
Selfish routing
Gametheory enabled multipleinput systems 
Planned learning activities and teaching methods:

Conventional lectures with slides/projector support.
Interaction via the moodle platform. 
Additional notes about suggested reading:

Several books treat game theory from a general point of view.
Just as a suggestion, you can use Tadelis' book as a reference from a general perspective. This ought to be integrated with other material about applications. MacKenzie and DaSilva's book is a good example, even though it is not mandatory to use a book to this end (material found to the internet could also work).
In any event, the lecturer will provide the students with additional booklets and all the lecture notes. 
Textbooks (and optional supplementary readings) 

S. Tadelis., Game Theory: An Introduction.. : Princeton., 2013.

A. MacKenzie, L. DaSilva, Game Theory for Wireless Engineers. : Morgan&Claypool, 2006.

Noam Nisan, Tim Roughgarden, Eva Tardos, Vijay V. Vazirani (eds.), Algorithmic Game Theory. : Cambridge Univ. Press, 2007.

Roberto Lucchetti, A Primer in Game Theory. : Esculapio, 2011.

Innovative teaching methods: Teaching and learning strategies
 Lecturing
 Problem based learning
 Working in group
 Story telling
 Problem solving
 Active quizzes for Concept Verification Tests and class discussions
 Loading of files and pages (web pages, Moodle, ...)
Innovative teaching methods: Software or applications used
 Moodle (files, quizzes, workshops, ...)
Sustainable Development Goals (SDGs)

