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 Algorithmic Game Theory
2. Module Code COMP559
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester Second Semester
7. CATS Level Level 7 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Dr GB Birmpas Computer Science G.Birmpas@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
Ms E Varloot Computer Science E.Varloot@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

  10

      40
17.

Private Study

110
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):

COMP323 Introduction to Computational Game Theory
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
 

1. To provide an understanding of the inefficiency arising from uncontrolled, decentralized resource allocation.
2. To provide a foundation for modelling various mechanism design problems together with their algorithmic aspects.
3. To provide the tools and paradigms for the design and analysis of efficient algorithms/mechanisms that are robust in environments that involve interactions of selfish agents.
4. To review the links and interconnections between algorithms and computational issues with selfish agents.
5. To provide an in-depth, systematic and critical understanding of selected significant topics related to algorithmic game theory, together with the related research issues.

 
28. Learning Outcomes
 

(LO1) Have a critical awareness ofcurrent problems, important concepts and research issues in  the field ofalgorithmic game theory. 

 

(LO2) Systematic knowledge andability to quantify the inefficiency of equilibria.

 

(LO3) Systematic knowledge andability to formulate mechanism design models or network games for the purpose of modeling particularapplications.

 

(LO4) Detailed understanding andability to use, describe and explain appropriate algorithmic paradigms and techniques in context of aparticular game-theoretic or mechanism design problem.

 

(LO5) Critical ability to read,understand and communicate research literature in the field of algorithmic game theory.  

 

(LO6) Critical ability torecognise potential research opportunities and research directions in the field of algorithmic game theory.

 

(S1) Communication (oral, written and visual) - Presentation skills – oral

 

(S2) Communication (oral, written and visual) - Presentation skills - written

 

(S3) Communication (oral, written and visual) - Presentation skills - visual

 

(S4) Critical thinking and problem solving - Critical analysis

 

(S5) Information skills - Critical reading

 

(S6) Business and customer awareness

 

(S7) Computer science principles

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Yes

Teaching Method 2 - Tutorial
Description:
Attendance Recorded: Yes

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 to Network Games: Reminder of game theory fundamentals (with a focus on network games): solution concepts such as Nash equilibria, correlated equilibria. (2 lectures)
Load balancing games: existence and complexity of equilibria, price of anarchy. (3 lectures)
Routing games (atomic and non-atomic selfish routing): existence and complexity of equilibria, price of anarchy, price of stability. (5 lectures)
Introduction to Mechanism Design: Social Choice, Mechanisms with Money, Dominant Strategies, Characterisations of Incentive Compatible Mechanisms, Bayesian-Nash Implementation. (4 lectures)
Mechanism Design without Money. (3 lectures)
Combinatorial Auctions (CA): Single-Minded Bidders, Bidding   Languages, Iterative Auctions, Winner Determination, Applications. (4 lectures)
Profit Maximisation in Mechanism Design. (3 lectures)
Online Mechanisms (2 Lectures)
Current Topics in Algorithmic Game Theory (Network Creation Games, Spon sored Search Auctions, Price of Anarchy in Auctions)

 
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
  (559) Written Exam There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :2nd Semester 150 70
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (559.1) Assessment 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2nd semester 0 15
  (559.2) Assessment 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2nd semester 0 15