SUMMARY OF INFORMATION ON EACH COURSE/MODULE
1.
Name of Course/Module/Subject
Game Algorithms
2.
3.
Course /Subject Code
Status of Subject
TGD 3351
4.
MQF Level/Stage
Bachelor – MQF Level 6
Specialization Core for B. CS (GD)
Note :
Certificate – MQF Level 3
Diploma – MQF Level 4
Bachelor – MQF Level 6
Masters – MQF Level 7
Doctoral – MQF Level 8
5.
Version
July 2009
(state the date of the last Senate approval)
6.
7.
8.
9.
Pre-Requisite/Requirement for Registration
TCP1201 Object-Oriented Programming & Data
Structures
Name(s) of academic/teaching staff
John See Su Yang
Wong Ya Ping
Semester and Year offered
Trimester 1 (Delta)
Objective of the course/module/subject in the programme :
To equip students with the fundamental algorithms and concepts in game programming and artificial
intelligence (AI) and to provide exposure to hands-on game development and application of relevant game
algorithms.
10.
Justification for including the subject in the program :
To provide students with knowledge of fundamental algorithms in game programming and exposure to
hands-on game development
11.
Subject Learning Outcomes :
LO1: Describe fundamental game
algorithms and artificial intelligence
used in game development
LO2: Explain game algorithms for
both front-end and back-end parts
of computer games
LO3: Apply usage of artificial
intelligence to accomplish complex
behaviours in games
LO4: Design specialised games
that utilise relevant state-of-the-art
game algorithms and artificial
intelligence
12.
Level
1
Cognitive
2
Cognitive
3
Cognitive
6
Mapping of Learning Outcomes to Programme Outcomes :
Learning Outcomes
LO1
LO2
LO3
LO4
13.
Domain
Cognitive
PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
X
X
X
X
X
Assessment Methods and Types :
CQAAE/FORM/07
Ver.1, Rev.0
01.06.2013
Page 1 of 4
Method and Type
Test
Assignment
Project
14.
Description/Details
Written test on algorithms and concepts
Hands-on (programming) take-home assignment
Game development prototype (applying relevant
algorithms learnt)
Percentage
20
20
60
Details of Subject
Mode of Delivery
Indicate
allocation of SLT (lecture, tutorial, lab) for each
subtopic
(eg : Lecture, Tutorial, Workshop, Seminar, etc.)
Topics
1. Introduction to Game Algorithms
& Programming
Overview of game algorithms, Game
Architecture: Software, Game logic,
Presentation, Programming.
Types, Structures, Classes, Data
Structures in Games.
2. Game Programming
Fundamentals
Sprites, Mapping matrices, Screen
swapping, Scrollers (2-way, 4-way,
Parallax), Isometric Engines (Pseudo3D). Cell Animation, Transformations
3. Collision Detection & Reaction
Geometry of Collision Detection, Point
Inclusion Tests, Various Bounding Box
methods: Rectangle Collision, Per-Pixel
Collision, Heightmap Collision
4. Overview of Game AI
Complexity of Game AI, Perception
Issues, Implementations of Game AI,
Constraints of Speed & Memory, AI
Engine
5. Movement
Basic Movement Algorithms,
Kinematics, Steering Behaviors, Group
Behaviors (Flocking Algorithms),
Combining Steering and Group
Behaviors
6. Pathfinding
Review of Graphs & Graph
Representations, Djikstra (Shortest
Path) Algorithm, A* Algorithm, MemoryEfficient Algorithms (IDA*, SMA*)
CQAAE/FORM/07
Ver.1, Rev.0
01.06.2013
Lecture (Hrs)
2
Lab (Hrs)
-
Tutorial (Hrs)
-
3
-
3
3
-
3
1
-
-
3
-
4
finding
4
-
4
Page 2 of 4
7. Decision Making
Decision Trees, Combination of
Decisions, Random Decision Trees,
Finite State Machines, Nondeterministic State Machines,
Hierarchical State Machines, Fuzzy
Logic, Fuzzy State Machines, GoalOriented Behavior, Rule-based
Systems
8. Tactical & Strategic AI
Waypoint Tactics, Tactical Pathfinding,
Influence & Visibility Maps,
Coordinated Action and Behavior in
Groups
9. Advanced AI Techniques
Learning & Predictive Methods:
Probabilistic Theory and Bayesian
Reasoning, Neural Networks
15.
16.
king 6
-
6
4
-
4
2
-
2
28
-
26
Total Student Learning
Face to Face
Independent
Time (SLT)
Learning
Lecture
28
28
Tutorials
26
26
Test
2
7
Assignment
20
Project
2 (for project progress update and consultation)
22
Sub Total
57
103
Total SLT
160
Credit Value
4
Reading Materials :
Reference Materials
Textbook
1. Millington, I., & Funge, J. (2009). Artificial
1. Bourg, D.M. & Seemann, G (2004). AI for
Game Developers, O’Reilly Media Publishing,
intelligence for games (2nd ed.). Morgan
Kaufmann, USA.
USA.
2. Buckland, M. (2005). Programming Game AI
by Example, Wordware Publishing, USA.
3. Carter, C. (2009). Microsoft XNA Game Studio
3.0 Unleashed, SAMS Publishing, USA.
CQAAE/FORM/07
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01.06.2013
Page 3 of 4
17.
Appendix (to be compiled when submitting the complete syllabus for the programme) :
1. Mission and Vision of the University and Faculty
2. Programme Objectives or Programme Educational Objectives
3. Programme Outcomes (POs)
4. Mapping of POs to the 8 MQF domain
5. Mapping of Los to the POs
6. Summary of the Bloom’s Taxonomy’s Domain Coverage in all the Los in the
format below :
Bloom’s Taxonomy Domain
Learning Outcomes
Subject
(please state the
learning Outcomes)
TGD3351
Affective
Cognitive
Learning Outcome 1
1
Learning Outcome 2
2
Learning Outcome 3
3
Learning Outcome 4
6
Psychomotor
7. Summary of LO to PO measurement
8. Measurement and Tabulation of result for LO achievement
9. Measurement Tabulation of result for PO achievement
Mapping Learning Outcome to Assessment
No.
Assessment
A1
Test (20%)
A2
Assignment (20%)
A3
Project (60%)
CQAAE/FORM/07
Ver.1, Rev.0
01.06.2013
LO1
LO2
X
X
X
LO3
LO4
X
X
X
Page 4 of 4