ITC364 Computational Intelligence (8)

Computational Intelligence is the study of the design of intelligent agents. This subject develops and links the theoretical and experimental aspects of the discipline. The subject explores the specification and design of intelligent agents, implementing, testing and improving real software systems for many challenging application domains. The application areas include: delivery robots, diagnostic assistants and information slaves. This subject will serve as an introduction to the more specialised Artificial Intelligence topics concerning neural networks, genetic algorithms, expert systems, machine learning and machine vision.

Subject Outlines
Current CSU students can view Subject Outlines for recent sessions. Please note that Subject Outlines and assessment tasks are updated each session.

No offerings have been identified for this subject in 2018.

Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System



One session


School of Computing and Mathematics

Enrolment Restrictions

Not available to students who have completed ITC528

Assumed Knowledge

Mathematical background at the level of MTH129

Programming background at the level of (ITC226 or ITC313 or ITC322)

Subject Relationships

ITC528 Paired Subject

Incompatible Subjects


Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to explain the basic components of an intelligent agent;
  • be able to apply the First-Order Logic approach to the fundamentals of computational intelligence;
  • be able to analyse how computational intelligence concepts are employed in various applications;
  • be able to design simple computational intelligence programs, and analyse more complicated ones;
  • be able to analyse the components of an expert system;
  • be able to explain the issues associated with agent learning.


This subject will cover the following topics:
  • Introduction to computational intelligence
  • Problem-solving by search strategies
  • Logical Agents and First-Order Logic
  • Agent action planning
  • Knowledge representation
  • Uncertain knowledge and reasoning
  • The theory of learning and machine learning
  • Probabilistic learning models


Current Students

For any enquiries about subject selection or course structure please contact Student Central or or phone on 1800 275 278.

Prospective Students

For further information about Charles Sturt University, or this course offering, please contact info.csu on 1800 275 278 (free call within Australia) or enquire online.

The information contained in the 2018 CSU Handbook was accurate at the date of publication: August 2018. The University reserves the right to vary the information at any time without notice.