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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

Offered

Clayton First semester 2009 (Day)

Synopsis

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.

Objectives

To acquire Knowledge and Understanding of:

  1. The role of intelligent decision support in organisations;
  2. Decision support paradigms and applications;
  3. Methods for handling certain and uncertain knowledge;
  4. Issues in the design and construction of intelligent decision support systems;
  5. Correctness, precision and scalability.

To develop the following Attitudes, Values and Beliefs:
  1. Recognition of the value of intelligent decision support within an organisation;
  2. Adoption of a critical approach to the choice of decision support method;
  3. Appreciation of the impact of data quality, and business constraints on the behaviour of a decision support system;
  4. Appreciation of the limitations of formal decision models and the handling of uncertainty.

To develop the following Practical Skills:
  1. Choose appropriate decision support methods;
  2. Separate modelling from solving;
  3. Implement simple decision support tools on a constraint programming platform;
  4. Combine methods to meet application requirements;
  5. 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:
  1. Document and communicate an intelligent decision support model;
  2. Work in a team during model design and implementation stages;
  3. Present a justification for choosing or combining decision support methods.

Assessment

Examination: 60%
Assignments, class tests and laboratory exercises: 40%
Students must pass the examination in order to pass the unit.

Contact hours

4 x contact hrs/week

Prerequisites

FIT1006 or ETC1000 and 24 points at first years

Additional information on this unit is available from the faculty at:

http://www.infotech.monash.edu.au/units/fit3022

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