|Module Title||AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE|
|Co-ordinator||Dr Mark Ratcliffe|
|Course delivery||Lecture||20 lectures|
|Practical||3 x 2 hours.|
|Supplementary examination||Will take the same form, under the terms of the Department's policy|
The module will provide students with an introduction to the problems and techniques of artificial intelligence.
To introduce students to the problems and techniques of artificial intelligence.
On completion of this module, students should be able to:
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.
** Consult For Futher Information
E. Rich and K. Knight. (1991) Artificial Intelligence. 2nd.. McGraw Hill,
Alison Cawsey. (1998) The Essence of Artificial Intelligence. Essence of Computing Series. Prentice Hall ISBN 0135717795
** Recommended Background
S.J. Russell and P. Norvig. (1995) AI: A Modern Approach. Prentice-Hall