|| CS26210 |
|| ARTIFICIAL INTELLIGENCE CONCEPTS |
|| 2001/2002 |
|| Dr Mark Ratcliffe |
|| Semester 1 |
|| Dr George Coghill |
|| CS16010 or CS14020 |
| Course delivery
|| Lecture || 17 lectures |
|| Practical || Up to 10 x 2hr |
|| Supplementary examination || Will take the same form, under the terms of the Department's policy. || |
|| Exam || 2 Hours || 100% |
|| http://www.aber.ac.uk/compsci/ModuleInfo/CS26210 |
Artificial Intelligence is the study of computer systems which can perform the sort of tasks that are usually associated with human intelligence. Examples are: chess playing, pattern recognition, speech understanding and problem solving. The aim of this module is to introduce the main ideas and current problems in Artificial Intelligence including the key concepts of knowledge representation, reasoning and expert systems. Students will be required to implement and utilise these concepts by means of an Artificial Intelligence programming language.
Artificial Intelligence (AI) has made many important contributions to computer science in general, and most experts believe AI techniques will become increasingly important. This module builds on the introduction to the fundamental concepts of AI given in CS16010 . Key issues including knowledge representation, reasoning and expert systems are addressed both theoretically and practically.
On successful completion of this module students will be able to:
describe the importance of propositional and predicate logic in Artificial Intelligence systems;
solve simple problems in propositional and first order predicate logic;
select and defend the use of particular search techniques in the solution of problems such as path planning;
appreciate the fundamentals of second generation expert system technology;
explain the conceptual basis of current attempts to overcome the limitations of first generation expert systems;
explain the function and use of fuzzy logic;
be capable of writing basic Artificial Intelligence programs in Lisp;
explain the application of Bayesian probabilty to simple reasoning scenarios.
1. Introduction - 1 Lecture
Revision of AI material covered in CS16010.
2. Introduction to Lisp - 2 Lectures
3. Advanced Search - 4 Lectures
Examination of the more advanced aspects of search in knowledge based systems. Game Playing.
4. Knowledge Representation and Inference - 4 Lectures
Propositional Logic and First Order Predicate Logic.
5. Uncertainty - 3 Lectures
Probabilistic Reasoning, Fuzzy Logic.
6. Expert Systems - 2 Lectures
Limitations of first generation systems. Characterising second generation expert systems.
7. Summary - 1 Lecture
Review and analysis of AI.
8. Lisp - up to 10 Practicals
Workshops on programming in and using Lisp.
** Should Be Purchased
S.J. Russell and P. Norvig. (1995)
AI: A Modern Approach. Prentice-Hall 0131038052
** Recommended Text
P. Winston and B. Horn. (1988)
LISP, Third Edition. Addison-Wesley 0201083191
Alison Cawsey. (1998)
The Essence of Artificial Intelligence. Essence of Computing Series. Prentice-Hall ISBN 0135717795
** Consult For Futher Information
C. J. Hogger. (1990)
Essentials of Logic Programming. Oxford University Press ISBN 0-19-853832-4
G. F. Luger and B. Stubblefield. (1997)
Artificial Intelligence. 3rd Ed.. Addison-Wesley ISBN 0805311963
Artificial Intelligence. 3rd Ed.. Addison-Wesley 0-201-83377-4
S. C. Shapiro. (1992)
Encyclopedia of Artificial Intelligence. Addison-Wesley 0471503007X