FIT3022 - Intelligent decision support systems
6 points, SCA Band 2, 0.125 EFTSL
Undergraduate Faculty of Information Technology
Leader(s): Clayton - Mark Wallace; Gippsland - Kai Ming Ting
Clayton First semester 2009 (Day)
The objective is to understand the role of intelligent decision support in organisations, paradigms and applications, dealing with uncertain data; system design and construction; to recognise of the value of intelligent decision support, to adopt a critical approach to the choice of method, to appreciate the impact of data quality, and business constraints on the behaviour of a decision support system, and the limitations of formal decision models; to separate modelling from solving, implement simple decision support tools on a constraint programming platform, combine methods to meet application requirements, and to assess the limitations in scalability and precision of a solution.
To acquire Knowledge and Understanding of:
- The role of intelligent decision support in organisations;
- Decision support paradigms and applications;
- Methods for handling certain and uncertain knowledge;
- Issues in the design and construction of intelligent decision support systems;
- Correctness, precision and scalability.
To develop the following Attitudes, Values and Beliefs:
- Recognition of the value of intelligent decision support within an organisation;
- Adoption of a critical approach to the choice of decision support method;
- Appreciation of the impact of data quality, and business constraints on the behaviour of a decision support system;
- Appreciation of the limitations of formal decision models and the handling of uncertainty.
To develop the following Practical Skills:
- Choose appropriate decision support methods;
- Separate modelling from solving;
- Implement simple decision support tools on a constraint programming platform;
- Combine methods to meet application requirements;
- Assess the limitations in scalability and precision of a solution.
In addition, it is expected that the following Relationships, Communication and Team Work skills will be developed and enhanced:
- Document and communicate an intelligent decision support model;
- Work in a team during model design and implementation stages;
- Present a justification for choosing or combining decision support methods.
Assignments, class tests and laboratory exercises: 40%
Students must pass the examination in order to pass the unit.
4 x contact hrs/week