Enrolments for this year have closed. Keep exploring subjects.
Subjects may require attendance
This research-based university in Perth has a strong interdisciplinary focus and a reputation for outstanding teaching and ground-breaking research. With more than 22,000 students and 2,000 staff from over 90 countries, and campuses in Dubai and Singapore, Murdoch embraces free thinking, shared ideas and knowledge to make a difference, and Open Universities Australia is certainly part of that.
QS RANKING 2020
Times Higher Education Ranking 2020
On successful completion of this unit you should be able to:
- demonstrate an understanding of basic intelligent systems concepts
- be able to explain the theory, operation and strengths and weaknesses of state machines, expert systems, fuzzy logic engines, neural networks, genetic algorithms data mining tools and intelligent agents
- be able to explain the strengths and weaknesses of state machines, expert systems, fuzzy logic engines, neural networks, genetic algorithms, data mining tools and intelligent agents
- be able to choose an appropriate intelligent technique to solve a given problem
- know how to use off-the-shelf intelligence tools, including expert system shells artificial neural network and other simulators for solving problems
- explain the importance of representation and search in problem-solving
- understand the role of applied knowledge in problem-solving
- be able to evaluate the capability of an intelligent system to solve a real problem.
- A week-by-week guide to the topics you will explore in this unit will be provided in your study materials.
- Online assignment submission
- Podcasting/Lecture capture
- Online Quizzes/Tests
- Resources and Links
- Printable format materials
You must have successfully completed the following subject(s) before starting this subject:
No special requirements
This unit offers an introduction to the fundamental concepts and techniques of artificial intelligence focusing on expert systems to solve engineering problems, data mining, data analysis for industries and intelligent agents in computer games. Topics include: introduction to artificial intelligence and applications; introduction to game AI; rule based expert systems; neural computing; fuzzy logic; genetic algorithms, intelligent agents, state machines and methods of evaluating these technologies.
- Invigilated Exam (50%)
- Outline and draft (10%)
- Report and Code (20%)
- Lab Work (20%)