Module Specification

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
1. Module Title Introduction to Computational Game Theory
2. Module Code COMP323
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester First Semester
7. CATS Level Level 6 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Professor PG Spirakis Computer Science P.Spirakis@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 30

  5

      35
17.

Private Study

115
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

COMP116 Analytic Techniques for Computer Science
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. Aims
 

To introduce the student to the notion of a game, its solutions, concepts, and other basic notions and tools of game theory, and the main applications for which they are appropriate, including electricity trading markets.

To formalize the notion of strategic thinking and rational choice by using the tools of game theory, and to provide insights into using game theory in modeling applications.

To draw the connections between game theory, computer science, and economics, especially emphasizing the computational issues.

To introduce contemporary topics in the intersection of game theory, computer science, and economics.

 
28. Learning Outcomes
 

(LO1) A student will understand the notion of a strategic game and equilibria, and understand the characteristics of main applications of these concepts;

 

(LO2) Given a real world situation a student should be able to identify its key strategic aspects and based on these be able to connect them to appropriate game theoretic concepts;

 

(LO3) A student will understand the key connections and interactions between game theory, computer science and economics;

 

(LO4) A student will understand the impact of game theory on its contemporary applications, and be able to identify the key such application areas;

 

(S1) Numeracy/computational skills - Problem solving

 

(S2) Critical thinking and problem solving - Creative thinking

 

(S3) Numeracy/computational skills - Reason with numbers/mathematical concepts

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description:
Teaching Method 2 - Tutorial
Description:

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Tutorial
Description: On-campus synchronous sessions

 
30. Syllabus
   

Introduction: Making rational choices: what is a game? strategy, preferences, payoffs; basic solution concepts; non-cooperative versus cooperative games; basic computational issues: finding equilibria and learning in games; typical application areas for game theory (e.g. Google's sponsored search, eBay auctions, electricity trading markets). (4 lectures)

Games with Perfect Information: strategic games (prisoner's dilemma, matching pennies); Nash equilibria: theory and illustrations (Cournot's and Bertrand's models of oligopoly, auctions); information about linear programming; mixed strategy equilibrium; zero-sum games; basic computational issues. (9 lectures)

Extensive Games with Perfect Information: repeated games (prisoner's dilemma); subgame perfect Nash equilibrium; computational issues. (3 lectures)

Mechanism Design: basics; social choice; Vickrey and VCG mechanisms (shortest paths); combinatorial auctions; profit maximization; applica tions in Computer Science. (5 lectures)

Modern Applications of Game Theory: Google's sponsored search; eBay auctions; market equilibria; price of anarchy; prediction markets; reputation systems; electricity trading markets.. (9 lectures)

 
31. Recommended Texts
  Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
 

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (323) Final exam 150 70
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (323.1) Class Test 1 Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :1st semester 0 15
  (323.2) Class Test 2 Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :1st semester 0 15