First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
COMPUTER ENGINEERING
Course unit
GAME THEORY
INP4064059, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
COMPUTER ENGINEERING
IN0521, Degree course structure A.Y. 2009/10, A.Y. 2018/19
N0
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination GAME THEORY
Department of reference Department of Information Engineering
E-Learning website https://elearning.dei.unipd.it/course/view.php?idnumber=2018-IN0521-000ZZ-2017-INP4064059-N0
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge LEONARDO BADIA ING-INF/03

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
SCP7079401 GAME THEORY LEONARDO BADIA SC1176
SCP7079401 GAME THEORY LEONARDO BADIA SC2377
INP4064059 GAME THEORY LEONARDO BADIA IN2371
INP4064059 GAME THEORY LEONARDO BADIA IN2371
INP4064059 GAME THEORY LEONARDO BADIA IN2371
INP4064059 GAME THEORY LEONARDO BADIA IN2371

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines INF/01 Computer Science 3.0
Educational activities in elective or integrative disciplines ING-INF/03 Telecommunications 3.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 6.0 48 102.0 No turn

Calendar
Start of activities 01/10/2018
End of activities 18/01/2019

Examination board
Board From To Members of the board
5 A.A. 2018/2019 01/10/2018 15/03/2020 BADIA LEONARDO (Presidente)
MILANI SIMONE (Membro Effettivo)
CALVAGNO GIANCARLO (Supplente)
CORVAJA ROBERTO (Supplente)
ERSEGHE TOMASO (Supplente)
GUGLIELMI ANNA VALERIA (Supplente)
LAURENTI NICOLA (Supplente)
ROSSI MICHELE (Supplente)
TOMASIN STEFANO (Supplente)
ZANELLA ANDREA (Supplente)
ZANUTTIGH PIETRO (Supplente)
ZORZI MICHELE (Supplente)
4 A.A. 2017/2018 01/10/2017 15/03/2019 BADIA LEONARDO (Presidente)
MILANI SIMONE (Membro Effettivo)
BENVENUTO NEVIO (Supplente)
CALVAGNO GIANCARLO (Supplente)
CORVAJA ROBERTO (Supplente)
ERSEGHE TOMASO (Supplente)
LAURENTI NICOLA (Supplente)
ROSSI MICHELE (Supplente)
TOMASIN STEFANO (Supplente)
VANGELISTA LORENZO (Supplente)
ZANELLA ANDREA (Supplente)
ZANUTTIGH PIETRO (Supplente)
ZORZI MICHELE (Supplente)

Syllabus
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 multi-objective multi-agent 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 multi-agent 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 1-3 person groups, on course-related topics applied to ICT. This is agreed half-way through the course together with the lecturer.

For all the students, in any event the exam also includes a mandatory open-book 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 (non-engineering students or students without regular attendance), the written test involves all of the four exercises.

If the written test is sufficient, non-engineering 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 ex-post 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
Zero-sum 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
First-price and second-price auctions
VCG principle
Cooperative games: the core, the Shapley value

Resource allocation
Utilities, choices, and paradoxes
Potential games, coordination
Bio-inspired algorithms
Evolutionary games
Cognitive networks
Selfish routing
Game-theory enabled multiple-input 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. Cerca nel catalogo
  • A. MacKenzie, L. DaSilva, Game Theory for Wireless Engineers. --: Morgan&Claypool, 2006. Cerca nel catalogo
  • Noam Nisan, Tim Roughgarden, Eva Tardos, Vijay V. Vazirani (eds.), Algorithmic Game Theory. --: Cambridge Univ. Press, 2007. Cerca nel catalogo
  • Roberto Lucchetti, A Primer in Game Theory. --: Esculapio, 2011. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Problem based learning
  • Working in group
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)

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