Overview

The aim of this unit is for students to understand and apply artificial intelligence concepts and techniques to solve complex problems within game environments and game development, focusing on challenges that do not have straightforward solutions.

Requisites

Prerequisites
COS20007 Object Oriented Programming

OR
SWE20004 Technical Software Development
OR
COS20011 Software Development in Java
OR
COS30016 Programming in Java *
OR
COS30043 Interface Design and Development

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
03-March-2025
01-June-2025
Last self-enrolment date
16-March-2025
Census date
31-March-2025
Last withdraw without fail date
24-April-2025
Results released date
08-July-2025

Learning outcomes

Students who successfully complete this unit will be able to:

  • Discuss and implement software development techniques to support the creation of AI behaviour in games, focusing on non-obvious problem-solving approaches.
  • Understand and utilise a variety of graph and path-planning techniques.
  • Design and create realistic movements for agents using steering force models to simulate natural and responsive behaviour.
  • Design and develop agents capable of planning actions that require adaptive problem-solving techniques and innovative solutions.
  • Combine multiple AI techniques to develop sophisticated game AI capable of solving intricate, multi-layered problems that arise in dynamic game environments.

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Live Online
Lecture		1.00 12 weeks 12
On-campus
Class		2.00 12 weeks 24
Online
Directed Online Learning and Independent Learning		1.00 12 weeks 12
Unspecified Activities
Independent Learning		8.50 12 weeks 102
TOTAL150

Assessment

Type Task Weighting ULO's
Portfolio Individual  60-70%  1,2,3,4,5 
Assignment Individual 30-40% 1,2,3,4,5

Content

  • Search and optimisation
  • Knowledge representation, reasoning systems, machine learning
  • Evolutionary systems, artificial neural networks, collective systems
  • Game theory, design and development, rule design, game balancing
  • Scripting methods
  • AI evaluation

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.