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Soft Computing PG (7197.5)

Level: Postgraduate Level
Credit Points: 3
HECS Bands: 2
Faculty: Faculty of Science and Technology
Discipline: Academic Program Area - Technology


Possible changes to your unit's learning activities and assessment items

For the remainder of 2020, resulting from Australian Government's directives requiring physical distancing and restrictions on movement because of the COVID-19 pandemic, any exams that are required for assessment in a unit will be online exams. Online exams may also use online proctoring to help assure the academic integrity of those exams. Please contact your unit convener with any questions.

While the University has made efforts to ensure that Unit Outlines reflect a unit’s learning activities and assessment items, any changes to Australian Government directives because of the COVID-19 pandemic may require changes to these during the semester to ensure the safety and well being of students and staff. These changes will not be updated in the published unit outline, but will be communicated to you via your unit’s UCLearn(Canvas) teaching site. Any changes made will continue to meet the unit’s learning outcomes, as described in the Unit Outline.

Unit Outlines

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  • Semester 2, 2020, ON-CAMPUS, BRUCE (195612) - View
  • Semester 2, 2019, ON-CAMPUS, BRUCE (185354) - View
  • Semester 2, 2018, ON-CAMPUS, BRUCE (181989) - View
  • Semester 2, 2017, ON-CAMPUS, BRUCE (166295) - View
  • Semester 2, 2016, ON-CAMPUS, BRUCE (151495) - View
  • Semester 2, 2015, ON-CAMPUS, BRUCE (139978) - View

If a link to your Unit Outline is not displayed, please check back later. Unit Outlines are generally published by Week One of the relevant teaching period.


This is an advanced unit in artificial intelligence emphasizing the Soft Computing discipline. Each semester, coverage is of two or three topics from Artificial Neural Networks, Fuzzy Systems, Genetic Algorithms, Software Agents, Artificial Life, and Complex Adaptive Systems. The unit content covers Soft Computing theory, fusion of two or more Soft Computing techniques and their applicability to real world applications. The choices depend on the availability of lecturers, student interest and research activity in the School. The unit has a strong practical focus with the implementation of Soft Computing techniques in laboratory exercises and assignments.

Learning Outcomes

On successful completion of this unit, students will be able to:

1. Describe, argue for and critique the Soft Computing discipline. Students will be able to use at least two of the Soft Computing techniques; and

2. Given an artificial intelligence project, a student will be able to: identify and select a suitable Soft Computing technology to solve the problem; construct a solution and implement a Soft Computing solution.

Assessment Items

Contact Hours

Up to thirty nine hours per semester.


8995 Software Technology 1 G



Assumed Knowledge

Basic mathematics.

Incompatible Units


Equivalent Units


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