University of Warsaw - Central Authentication System

Optimization and game theory

General data

Course ID:	1000-715bOTG
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	Optimization and game theory
Name in Polish:	Optymalizacja i teoria gier
Organizational unit:	Faculty of Mathematics, Informatics, and Mechanics
Course groups:	Obligatory courses for 2nd year Bioinformatics
ECTS credit allocation (and other scores):	4.50 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	obligatory courses
Prerequisites (description):	multidimensional analysis and ordinary differential equations
Short description:	The lecture encompasses optimization in multidimensional spaces and noncooperative game theory
Full description:	The lecture consists of – Elements of differential calculus for functions of many variables important for optimization: extended Sylvester theorem, convexity and concavity; – Elements of multidimensional optimization both with and without constraints (including necessary Karush–Kuhn–Tucker conditions for various form of constraints and sufficient conditions), discrete time dynamic optimization and Bellman equation; – Elements of game theory (games in extensive and normal form, dominant and dominated strategies, reduction of the game for extensive and normal form, Nash equilibrium, including subgame-perfect Nash equilibrium, minmaks and optimal/minimax,l strategies, pure and mixed strategies, evolutionary stable strategies, replicator dynamics.
Bibliography:	(in Polish) M. Malawski, A. Wieczorek, H. Sosnowska. Konkurencja i kooperacja. Teoria gier w ekonomii i naukach społecznych. Wydawnictwa Naukowe PWN, 2012; P.D. Straffin, Teoria gier, Scholar, 2004; J. Palczewski, Skrypt Optymalizacja II, http://mst.mimuw.edu.pl/lecture.php?lecture=op2;
Learning outcomes:	Students know and understand methods of optimization, including nonlinear optimization and tools of noncooperative game theory within the scope of the lecture. They can calculate extrema of functions of many variables (with or without constraints) (K_U05), find Nash equilibria, dominant and dominated strategies, minimax and ESS (or to show that they do not exist)
Assessment methods and assessment criteria:	final exam

Classes in period "Winter semester 2023/24" (past)

Time span:	2023-10-01 - 2024-01-28	Selected timetable range: weekly course term Navigate to timetable MO TU W TH FR WYK CW
Type of class:	Classes, 30 hours more information Lecture, 30 hours more information
Coordinators:	Agnieszka Wiszniewska-Matyszkiel
Group instructors:	Agnieszka Wiszniewska-Matyszkiel
Students list:	(inaccessible to you)
Examination:	Examination

Classes in period "Winter semester 2024/25" (future)

Time span:	2024-10-01 - 2025-01-26	Selected timetable range: weekly course term Navigate to timetable
Type of class:	Classes, 30 hours more information Lecture, 30 hours more information
Coordinators:	Agnieszka Wiszniewska-Matyszkiel
Group instructors:	Agnieszka Wiszniewska-Matyszkiel
Students list:	(inaccessible to you)
Examination:	Examination

Course descriptions are protected by copyright.
Copyright by University of Warsaw.