Module Details

Module Code: GAME
Module Title: Artificial Intelligence for Games
Title: Artificial Intelligence for Games
Module Level:: 8
Credits:: 5
Module Coordinator: Nigel Whyte
Module Author:: Oisin Cawley
Domains:  
Module Description: To immerse students in the formal theory, and the application of contemporary techniques in Artificial Intelligence for computer games development.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Compare and contrast a number of search techniques including within adversarial environments
LO2 Illustrate different techniques for modelling/implementing the Game space
LO3 Apply appropriate AI techniques to enhance the Gaming experience
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is recommended before enrolment in this module.
No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Additional Requisite Information
No Co Requisites listed
 
Indicative Content
What is Intelligence?
Turing Test. Chinese Room. Philosophical Implications, AI in Games Context.
Basic Behaviours
Flocking, Swarming, Chasing, Evading.
Group Behaviours
Flocking, Swarming, Coordinated movements, Squads
Search
Search space, Basic search algorithms, Heurisitc Search, A* Search, Advanced A* variants
Game Search
Mini-max search, alpha-beta search, search space pruning
Basic Decision Making
Finite State Machines, Decision Trees
Fuzzy Logic
Fuzzification, Fuzzy Rule Application, Defuzzification, Combs Method
Module Content & Assessment
Assessment Breakdown%
Continuous Assessment35.00%
Project15.00%
End of Module Formal Examination50.00%

Assessments

Full Time

Continuous Assessment
Assessment Type Case Studies % of Total Mark 35
Timing n/a Learning Outcomes 1,2,3
Non-marked No
Assessment Description
Students are required to implement specific algorithms within a gaming context
Project
Assessment Type Project % of Total Mark 15
Timing n/a Learning Outcomes 1,2,3
Non-marked No
Assessment Description
Intended as a group project
No Practical
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 50
Timing End-of-Semester Learning Outcomes 1,2,3
Non-marked No
Assessment Description
A written assessment of student's understanding and ability to conceptually apply the course material appropriately.
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

SETU Carlow Campus reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Category Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact 2 Lectures per week 12 Weeks per Stage 2.00 24
Laboratory Contact 2 Laboratory sessions per week 12 Weeks per Stage 2.00 24
Estimated Learner Hours Non Contact Estimated Learner Hours 15 Weeks per Stage 5.13 77
Total Weekly Contact Hours 4.00
 
Module Resources
Recommended Book Resources
  • Ian Millington. Artificial Intelligence for games, Morgan Kaufman, [ISBN: 978-012374731].
  • George Luger. Artificial intelligence, Harlow, England ; Addison-Wesley, 2002., [ISBN: 0201648660].
  • Stuart J. Russell and Peter Norvig; contributing writers, John F. Canny... [et al.]. (2003), Artificial intelligence, Prentice Hall/Pearson Education, Upper Saddle River, N.J., [ISBN: 978-0130803023].
  • Mat Buckland. Programming Game AI By Example, Wordware Publishing, p.495, [ISBN: 9781556220784].
  • David M. Bourg and Glenn Seemann. (2004), AI for game developers, O'Reilly, Sebastopol CA, [ISBN: 9780596005559].
This module does not have any article/paper resources
This module does not have any other resources
Discussion Note: