UnitLevel 3Undergraduate

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 2021 in Semester 1 at Clayton. It has no prerequisites.

Credit points
6
Offered in 2021
Semester 1
Clayton
Assessment
Exam 40%
and 3 other tasks
Workload
144 hours
per semester

This is the 2021 handbook entry. See the 2024 entry.

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Requisites

Before FIT3094

No prerequisites or corequisites besides the enrolment rules below.

After FIT3094

No unit lists FIT3094 as a prerequisite in the 2021 handbook.

Enrolment rules

Prerequisites: FIT2049 or FIT2096

Overview

This unit introduces topics in Artificial Intelligence (AI) suited to real-time simulation and computer games development. Using a practice-based and programming-led approach, the unit explores a number of fundamental concepts, 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 simulation, bio-inspired intelligence models and search algorithms. Programs are developed using the Processing environment in Java or C++.

Offerings in 2021

Teaching periodCampusMode
First semesterClaytonOn campus

Assessment

  • Assignment 1: Path FindingAssignmentThreshold hurdle
    20%
  • Assignment 2: Agent Decision Making and PlanningAssignmentThreshold hurdle
    20%
  • Assignment 3: EvolutionAssignmentThreshold hurdle
    20%
  • Scheduled final assessment (2 hours and 10 minutes)ExamThreshold hurdle
    40%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Select, evaluate and apply AI software techniques to model simple intelligent behaviour in 2D discrete simulations and games;

  2. 2

    Select, evaluate and apply AI software techniques to model simple intelligent behaviour in 3D continuous simulations and games;

  3. 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. 4

    Apply methods of embodied intelligence and physicality to the development of intelligent behaviour in physical artefacts;

  5. 5

    Apply - through practice-based learning - design, development, execution and validation of real-time interactive software using AI techniques.

Workload and teaching

  • Studio activities24 hours
  • Lectures24 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 activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning and online engagement.

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 5 areas of study in the 2021 handbook.

Contacts

Chief Examiners
Associate Professor Alan Dorin

Common questions

What are the prerequisites for FIT3094?

FIT3094 has no prerequisites, but enrolment rules apply.

When is FIT3094 offered?

In 2021, 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?

Yes. The exam is worth 40% of the final mark, alongside 3 other tasks.

Which majors and minors include FIT3094?

FIT3094 is part of Advanced computer science, Computational science, Games development and Software engineering.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Information Technology
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Available
Handbook years
20202021202220232024