FIT3080 - Intelligent systems - 2019

6 points, SCA Band 2, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.


Information Technology

Chief examiner(s)

Professor Ingrid Zukerman

Unit guides



  • Second semester 2019 (On-campus)


  • Second semester 2019 (On-campus)


FIT2004 or CSE2304


CSE2309, CSE3309, DGS3691


This unit includes history of artificial intelligence; intelligent agents; problem solving and search (problem representation, heuristic search, iterative improvement, game playing); knowledge representation and reasoning (extension of material on propositional and first-order logic for artificial intelligence applications, planning, frames and semantic networks); reasoning under uncertainty (belief networks); machine learning (decision trees, Naive Bayes, neural nets and genetic algorithms); language technology.


At the completion of this unit, students should be able to:

  1. describe the historical and conceptual development of AI; foundational issues for AI, including the frame problem and the Turing test;
  2. explain, apply and evaluate the goals of AI and the main paradigms for achieving them including logical inference, search, machine learning and Bayesian inference;
  3. explain the social and economic roles of AI;
  4. describe, analyse, apply and evaluate heuristic AI for problem solving;
  5. describe, analyse and apply basic knowledge representation and reasoning mechanisms;
  6. describe, analyse and apply probabilistic inference mechanisms for reasoning under uncertainty;
  7. describe, analyse, apply and evaluate machine learning techniques;
  8. describe, analyse, apply and evaluate the use of the above techniques in different domain, specifically language technology.


NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 3 hours and 10 minutes.

Examination (3 hours): 60%; In-semester assessment: 40%

Workload requirements

Minimum total expected workload equals 12 hours per week comprising:

  1. Contact hours for on-campus students:
    • Two hours of lectures
    • One 2-hour laboratory
  2. Additional requirements (all students):
    • A minimum of 9 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit applies to the following area(s) of study