SYS3540

Intelligent decision aids

F Burstein

6 points
* 4 hours per week
* First, second semester
* Caulfield, Clayton
* Corequisities: SYS3001 or SYS3050 or SYS3054
* Prohibitions: CFR3062, CFR3306, SYS3060, SYS3064, SYS4540

Objectives At the completion of this subject, students will have knowledge of a range of models and techniques for intelligent decision support and have an understanding of the application of these techniques to business decision situations. They will have developed the skills to build a prototype of an intelligent decision support system using packaged software incorporating these techniques, and will have developed attitudes regarding the appropriate use of intelligent decision aids.

Synopsis Decision making is an area where problems are often complex, vague, expressed in linguistic terms, subject to various biases and where information is fuzzy and incomplete. Intelligent decision support recognises that there is a need for computational methods which have the ability to learn from the environment, reason, reuse knowledge, and manage uncertainty. Intelligent decision aids include techniques originating from artificial intelligence such as knowledge-based systems, case-based systems, neural networks, genetic algorithms, and fuzzy logic. This subject addresses the application of these computational methods to decision support. Topics covered include the following. Models of intelligent decision support: normative models of intelligent decision support, descriptive models of intelligent decision support, models for handling uncertainty, the implications of these models for decision making and decision makers. Intelligent decision aids: rule-based expert systems, fuzzy expert systems, learning in decision support systems, learning from examples using neural networks, genetic algorithms as decision aids for optimisation problems. There will be a strong emphasis on the development and application of decision aids using these techniques in business and industry. The students will develop a prototype intelligent decision aid using packaged software incorporating these techniques.

Assessment Examination: 60%
* Practical work: 40%

Recommended texts
Goonatilake S and Treleaven P (eds) Intelligent systems for finance and business Wiley, 1995
Dhar V and Stein R Intelligent decision support methods: The science of knowledge work Prentice-Hall, 1997