Module Identifier CSM6010  
Module Title ARTIFICIAL INTELLIGENCE  
Academic Year 2000/2001  
Co-ordinator Dr Myra Wilson  
Semester Semester 2  
Co-Requisite CSM0320  
Course delivery Lecture   20 Hours  
  Practical   3 x 2 hours  
Assessment Exam   2 Hours   100%  
  Resit assessment   Supplementary examination will take the same form, under the terms of the Department's policy.   100%  

General description
This module concentrates on the technology and methodology of artificial intelligence (AI) practice. The aim is to show how practical knowledge-based systems can be implemented, developed and evaluated.

Aims
This course aims to give students a good understanding of a variety of AI systems, from expert systems through machine learning to adaptive computing. This will enable them to appreciate what current AI systems can and cannot do, and the circumstances in which their use is appropriate.

Learning outcomes
On completion of this module, students should be able to:

Syllabus
1. Introduction to AI - 2 Lectures
What is AI? Introduction to the range of applications of AI. What do we need AI for and how do we use it?

2. Intelligent Agents - 2 Lectures
How can we build an intelligent robot? Sensing, Action and Cognition. The symbolic approach. Memory, representation and reasoning.

3. Machine Vision - 3 Lectures
How can robots see? The nature of the vision task. Computer vision and image processing.

4. Expert Systems - 3 Lectures
How can human expertise be automated? Example applications and commercial successes. How to build an expert system - system concepts and architectures. Rule-based systems: design, operation and worked examples. Knowledge bases and knowledge based systems.

5. Search and reasoning - 5 Lectures
Why do we need search? Evaluation of search strategies. Un-informed search techniques. Informed search techniques. Networks and Frames. Reasoning and inference.

6. Machine Learning - 3 Lectures
How can a computer program learn? Neural nets. Pattern recognition. Inductive learning. Structural methods. Genetic algorithms.

7. Learning application - 2 Lectures
Case-based reasoning. Data mining.

Reading Lists
Books
** Should Be Purchased
SJ Russell and P Norvig. (1995) AI: A Modern Approach. Prenctice-Hall ISBN: 0131038052
** Consult For Futher Information
Alison Cawsey. (1998) The Essence of Artificial Intelligence. Essence of Computing Series. Prentice Hall, ISBN: 0135717795
P. H. Winston. (1992) Artificial Intelligence. 3rd. Addison Wesley
E. Rich and K. Knight. (1991) Artificial Intelligence. 2nd. McGraw Hill