Intelligent decision aids
I Jagielska
6 points
* 3 hours per week
* Second semester
* Caulfield
Objectives At the completion of this subject students should understand the need for computational methods that are tolerant of imprecision, uncertainty and partial truth; know about the basic theory and applications of fuzzy logic, neural networks and genetic algorithms; and be able to build decision support tools using neural networks, fuzzy systems and genetic algorithms.
Synopsis Decision making is one of the areas 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 are tolerant of imprecision, uncertainty and partial truth. These methods include fuzzy logic, neural networks and genetic algorithms. This subject addresses the application of these to intelligent decision support (IDSS). There will be a strong emphasis on the development and application of decision support tools using these techniques in business and industry. The following topics will be covered: uncertain knowledge and reasoning, fuzzy logic and its application, decision making in fuzzy environments, building fuzzy expert systems using fuzzy logic software, neural networks, developing applications using neural network simulators, genetic algorithms, application of genetic algorithms to optimisation problems; hybrid systems. The students will develop prototype intelligent decision aids using packaged software incorporating these techniques.
Assessment Practical work: 60%
* Unit test: 40%
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