Use the Tab and Up, Down arrow keys to select menu items.
In this paper, students will learn about game engine design through the use of existing engine source code. Students will extend existing functionality through the use of programming techniques. In addition, students will become comfortable designing and creating game-based artificial intelligence (AI) constructs.
Theoretical Learning OutcomesStudents will: Be able to explain the evolution of AI in the gaming context.Understand and be able to apply various AI methods such as Minimax and Monte Carlo tree search in board games, kinematic movement algorithms, Dijkstra, A*, and hierarchical pathfinding, behaviour trees, and Markov systems.Gain a basic understanding of Naïve Bayes Classifiers, decision tree learning, reinforcement learning, and neural networks.Have a better understanding of the procedural content generation and be able to provide examples of its application in games.Learn the functionalities of the game engine components covered in this course and how they work together such as human interface devices, gameplay systems, and physics engine.Be able to explain the basics of game networking.Practical Learning OutcomesStudents will: Be able to implement and modify AI methods learned in the Unity engine.Be able to debug and optimise in the Unity development environment.Learn how to create basic plug-in for Unity.Be able to use Havok physics with the Unity engine.
Please note that the timetable has not been finalised.
Scheduled days and times will be confirmed, following review, on 5th November.
Students must attend one activity from each section.
Participation (1% each) Weekly (excl. 7, 12) 10% (each presentation worth 5%) Laboratory (2% each) Weekly (excl. 6, 12) 20%(each challenge worth 5%)Assignment 1 Week 7 20%Assignment 2 Week 12 20%Final Test Week 12 30%
De Byl, Penny;
Holistic game development with Unity : an all-in-one guide to implementing game mechanics, art, design, and programming
CRC Press, 2019.
Game engine architecture
CRC Press, Taylor & Francis Group, 2018.
Artificial intelligence for games
Elsevier ; , 2006.
Yannakakis, Georgios N. , Togelius, Julian., SpringerLink (Online service);
Artificial Intelligence and Games
Springer International Publishing : Imprint : Springer, 2018.
Domestic fee $892.00
International fee $4,563.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see
School of Product Design on the
department and colleges