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COMP3477: ALGORITHMIC GAME THEORY

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Type	Open
Level	3
Credits	10
Availability	Available in 2023/24
Module Cap	None.
Location	Durham
Department	Computer Science

Prerequisites

COMP2181 Theory of Computation

Corequisites

None

Excluded Combinations of Modules

None

Aims

The aim of the module is to introduce the student to the notion of a game, relevant concepts, and other basic notions and tools of game theory, as well as the main applications where such concepts are used and applied.

Content

Introduction to Game Theory: what is a game? Strategy, preferences, payoffs.
Bimatrix games: strategies and payoffs; Nash equilibria.
Extensive games with Perfect Information.
Mathematical and algorithmic foundations of market equilibria.
Routing Games on Networks; Congestion Games.
Mechanism design and Combinatorial Auctions.

Learning Outcomes

Subject-specific Knowledge:

On completion of the module, students will be able to demonstrate:
An understanding of key game theoretic notions and ideas, and their connections to computer science and economics.
An understanding of the impact of game theory and mechanism design on contemporary applications.

Subject-specific Skills:

On completion of the module, students will be able to demonstrate:
The ability to apply techniques and methods from algorithmic game theory to tackle fundamental game theoretic problems.
The ability to identify key strategic aspects of real-world scenarios and model those scenarios as strategic games.
The ability to conduct review and self-study to further their knowledge beyond the taught material.

Key Skills:

On completion of the module, students will be able to demonstrate:
The ability to think critically.
The ability to work with abstract problems.
The ability to undertake general problem solving.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Lectures provide the material required to be learned and the application of the theory to practical examples.
Formative exercises are given to the students to assess their understanding of the taught material.
A piece of summative assessment tests the knowledge acquired and the students' ability to use this knowledge to solve game theoretic problems.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total
lectures	20	2 per week	1 hour	20
preparation and reading				80
total				100

Summative Assessment

Component: Coursework		Component Weighting: 100%
Element	Length / Duration	Element Weighting	Resit Opportunity
Summative Assignment		100	No

Formative Assessment

Example formative exercises are given during the course.

More information

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