|Lecturers:||Dr Manuela Dal Borgo|
|Most suitable for:||Sciences and Engineering and Societies|
|Mode of assessment:||2 hour unseen examination (60%), plus two 1,500 homework assignments worth 20% each|
|Taught:||Term 2 of Year 2|
Lectures: 11am-1pm on Tuesday and 1-2pm on Thursday
Workshop*: 10-11am on Thursday or 11am-12pm on Thursday or 12-1pm on Thursday
* Students are automatically allocated to a seminar class, so it is not possible to pick one. Students will only be permitted to change class if they have a clash with another class.
|Pre-requisites:||BASC0003 or an equivalent basic calculus and probability course. The mathematics involved is very basic, however ideal candidates are students who are prepared to be creative with mathematics.|
|Module level:||Level 5|
|Credit value:||15 credits|
What do wars, elections, job-hunting, couples, parenting, disease, stock markets, pistol duels, art valuations and YOU buying an apple from a street vendor have in common? The answer is Game Theory. All of these cases require that the people involved devise plans of action to achieve a goal; be it a victory in war or in an election, a higher paying job, a happier relationship, the containment of a biological attack or the lowest price YOU can pay for that apple!
Game theory is a mathematical theory of interaction, which is used to predict future outcomes. This module – an interdisciplinary introduction to game theory - is a bridge between the world of mathematics and science and the world of the humanities and the social and historical sciences. Students are introduced to game theory as a descriptive tool that is not bound by the topics of any single discipline. The power of game theory as a descriptive theory has historically been enhanced by various disciplines, which over the years have contributed new solution concepts. The most influential discoveries made in philosophy, politics, economics, finance, war studies, biology, psychology, law and history will be discussed.
Game theory has two components; a descriptive theory coupled with a solution theory. Students will be familiarized with the methods used to describe strategic and dynamic games of complete and incomplete information, in addition to the descriptive theories of voting, auctions, bargaining and evolutionary games. Students should also be able to apply the solution concepts (i.e. algorithms used to make predictions) of dominance, Nash equilibrium (NE), mixed strategy NE, sub-game perfect NE, Bayesian NE and finally pooling and separating equilibria. By the end of the course, students should be able to reproduce a variety of basic formal arguments, which we call games, coupled with elegant solutions.
The 20 or so games discussed in the module are meant to empower students with an extra tool-kit which they can use in their pathway studies, and later in their professional careers, to argue persuasively for or against a predicted scenario. This is an ideal module for students who wish to pursue careers in competitive environments where teamwork is essential (e.g. politics, finance, entrepreneurship).
Students enrolled on the module can view more information on Moodle.