Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2024-2025

Module COMP3477: ALGORITHMIC GAME THEORY

Department: Computer Science

COMP3477: ALGORITHMIC GAME THEORY

Type Open Level 3 Credits 10 Availability Available in 2024/2025 Module Cap None. Location Durham

Prerequisites

  • COMP2181 Theory of Computation

Corequisites

  • None

Excluded Combination 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/Hours
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.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University