Game Theory with Uncertainty

Code:

M4049

Acronym:

M4049

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2018/2019 - 2S

Active?	Yes
Responsible unit:	Department of Mathematics
Course/CS Responsible:	Master in Mathematical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:ENM	6	Official Study Plan since 2013-2014	1	-	6	56	162
			2
M:M	6	Plano de Estudos do M:Matemática	1	-	6	56	162

Teaching language

English

Objectives

The main objective of the course is to introduce in a rigorous way the fundamentals of Game Theory, with particular emphasis on Nash equilibria.

Learning outcomes and competences

It is pretended that the students are able to deal with the main concepts of game theory and the mathematical tools that are more relevant to its analysis

Working method

Presencial

Program

Static and dynamic games of complete and incomplete information; mechanism design and the revelation principle; perfect bayesian equilibrium in multi-stage games of incomplete information; signaling games; stochastic games; differential games; evolutionary dynamics; introduction to general equilibrium theory; applications to energy.

Mandatory literature

Drew Fudenberg and Jean Tirole; Game Theory, MIT Press, 1991
Robert Gibbons; A Primer in Game Theory, Prentice Hall – Financial Times. ISBN: 0-7450-1159-4
Josef Hofbauer, Karl Sigmund; Evolutionary Games and Population Dynamics, Cambridge University Press. ISBN: 0-521-62365-0
A. N. Yannacopoulos; Aspects of stochastic control in Finance and Economics, 2012
Aloísio Araújo; Introdução à Economia Matemática, IMPA, 1983

Complementary Bibliography

Deepak Rajagopal, Gal Hochman, and David Zilberman; A Simple Framework for Regulation of Biofuels, Springer , 2010
Deepak Rajagopal and David Zilberman; Environmental Lifecycle Assessment for Policy Decision-Making and Analysis, Farm Foundation, 2008
Gal Hochman, Steven Sexton and David Zilberman; The Economics of Trade, Biofuel, and the Environment, 2009
Daron Acemoglu, Philippe Aghion, Leonardo Bursztyn and David Hemous; The Environment and Directed Technical Change
K. J. Arrow, H. B. Chenery, B. S. Minhas and R. M. Solow; Capital-Labor Substitution and Economic Efficiency, 1961
R. Soeiro, A. Mousa, T. Oliveira and A. A. Pinto ; Dynamics of Human Decisions. Accepted for publication, Journal of Dynamics and Games, (2012) 1-25
M. Peixoto, A. A. Pinto, and D. Rand, editors. ; Dynamics, Games and Science I and II. Springer Proceedings in Mathematics series 1 and 2 (2011), Chapter 21, 339-352.
A. A. Pinto. ; Duopoly Models and Uncertainty. Interdisciplinary Applied Mathematics series. Springer-Verlag (in conclusion).

Teaching methods and learning activities

Presentation of the topics of the course and scientific discussion with the students

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation	Weight (%)
Participação presencial	50,00
Trabalho escrito	50,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Apresentação/discussão de um trabalho científico	4,00
Elaboração de projeto	26,00
Estudo autónomo	66,00
Frequência das aulas	56,00
Total:	152,00

Eligibility for exams

Unconditional

Calculation formula of final grade

The written work is worth 50 %, and the oral presentation is worth the other half.