Module Details

Module Code: DATA
Module Title: Data Structures and AI Algorithms
Title: Data Structures and AI Algorithms
Module Level:: 7
Credits:: 5
Module Coordinator: Nigel Whyte
Module Author:: Ross Palmer
Domains:  
Module Description: To give the learner an understanding of complex data structures and algorithms and their applications in computer games.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Use data structures and algorithms from an existing professional library
LO2 Design and implement a selection of common data structures and algorithms using object-oriented techniques
LO3 Describe and implement various pathfinding techniques
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
Templates
Introduction to templates and core concepts of the Standard Template Library
Common Containers
Linked lists; queues; priority queues; maps; hash tables.
Graph theory
Directed and undirected graphs; weighted graphs; graph representations; graph traversal algorithms.
Pathfinding
Breadth-first search, depth-first search, shortest path algorithms, A* pathfinder.
Module Content & Assessment
Assessment Breakdown%
Project20.00%
Practical40.00%
End of Module Formal Examination40.00%

Assessments

Full Time

No Continuous Assessment
Project
Assessment Type Project % of Total Mark 20
Timing Week 11 Learning Outcomes 3
Non-marked No
Assessment Description
Implementation of shortest-path pathfinding algorithm.
Practical
Assessment Type Practical/Skills Evaluation % of Total Mark 40
Timing n/a Learning Outcomes 1,2,3
Non-marked No
Assessment Description
Participation in and completion of practical work.
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 40
Timing End-of-Semester Learning Outcomes 1,2,3
Non-marked No
Assessment Description
90 minute written examination.
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 No Description 12 Weeks per Stage 1.00 12
Laboratory Contact No Description 12 Weeks per Stage 4.00 48
Estimated Learner Hours Non Contact No Description 15 Weeks per Stage 4.33 65
Total Weekly Contact Hours 5.00
 
Module Resources
Supplementary Book Resources
  • Allen Sherrod. (2007), Data Structures and Algorithms for Game Developers, Cengage Learning, p.560, [ISBN: 978-158450495].
  • Millington I.. (2019), AI for Games, Third. CRC Press, [ISBN: 978-113848397].
  • Cortez, D.. (2013), Data Structures and Design Patterns for Games, Cengage Learning, Inc, USA, [ISBN: 9781133603610].
This module does not have any article/paper resources
Other Resources
Discussion Note: