FIT3094 Artificial life, artificial intelligence and virtual environments
Faculty of Information Technology
FIT3094 Artificial life, artificial intelligence and virtual environments is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2023 in Semester 1 at Clayton. It needs FIT2096.
- Credit points
- 6
- Offered in 2023
- Semester 1
- Clayton
- Assessment
- No exam
- 4 tasks
- Workload
- 144 hours
- per semester
This is the 2023 handbook entry. See the 2024 entry.
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Requisites
Before FIT3094
Prerequisites
Pass these before you enrol.
After FIT3094
No unit lists FIT3094 as a prerequisite in the 2023 handbook.
Overview
This unit introduces topics in Artificial Intelligence (AI) and Artificial Life (ALife) suited to real-time simulation and computer games development. Using a practice-based and programming-led approach, the unit explores elements of the history of these fields, and their application to games, the fields’ fundamental concepts and theory, as well as practical techniques and algorithms that can be used to build real-time, interactive games, virtual environments and simulations. Starting with basic concepts in 2D discrete simulation, the unit progresses to continuous 3D models, agent-based models, bio-inspired intelligence and search algorithms. Programs are developed primarily using C++.
Offerings in 2023
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | On campus |
Assessment
- Assignment 1: Path FindingAssignment25%
- Assignment 2: Agent Decision Making and PlanningAssignment25%
- Assignment 3: EvolutionAssignment25%
- Weekly assessment tasksOther25%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Explain the concepts and theories underlying AI and Artificial Life;
- 2
Evaluate and apply AI and/or ALife software techniques to model simple intelligent behaviour in discrete and continuous simulations and games
- 3
Apply evolutionary algorithms to devise novel agents and understand their application, and that of other search algorithms, to problems requiring the search of a solution space;
- 4
Apply - through practice-based learning - design, development, execution and validation of real-time interactive software using AI techniques
Workload and teaching
- Lectures24 hours
- Studio activities24 hours
- Teaching approachActive learning
- Teaching approachPeer assisted learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.
Learning resources
Technology resources
Visual Studio 2017 OR 2019 Community Edition (Windows Only) https://visualstudio.microsoft.com/vs/
On-campus students may use the software which is installed in the computing labs. Information about computer use for students is available from the ITS Student Resource Guide in the Monash University Handbook.
Where it fits
FIT3094 is part of 3 areas of study in the 2023 handbook.
Contacts
- Chief Examiners
- Associate Professor Alan Dorin
- Unit Coordinators
- Dr Daniel Harabor
Common questions
What are the prerequisites for FIT3094?
You need FIT2096 before you enrol.
When is FIT3094 offered?
In 2023, FIT3094 runs in Semester 1 at Clayton.
How much work is FIT3094?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT3094 have an exam?
No. FIT3094 has 4 assessment tasks and no exam.
Which majors and minors include FIT3094?
FIT3094 is part of Advanced computer science, Computational science and Software engineering.