General description
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 and reasoning, expert systems and learning are addressed both theoretically and practically.

Aims
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.

Learning outcomes
On successful completion of this module students will be able to:

• describe the importance of a range of knowledge representations and their role in Artificial Intelligence systems;

• use search in the solution of problems such as path planning;

• explain the fundamentals of first generation expert system technology, and the conceptual basis of current attempts to overcome its limitations;

• explain the function and use of fuzzy logic;

• be capable of implementing basic Artificial Intelligence algorithms in Lisp.

Syllabus
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
Issues in knowledge representation: First Order Predictive 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 - 10 Practicals
Workshops on programming in and using Lisp.