Course Structure

The first four lectures will be given over to Prolog. This follows on from the three weeks of two hour lab sessions, and one supplementary exercise set in the winter term. A second supplementary evidence exercise in programming with Prolog will be set to be handed in friday, 23rd February. For the main part, the notes have already been given out during the practical session. So, in this document, sections of the notes on Prolog will be referenced rather than copied (saving some paper).

The last six lectures will cover the basic AI content of the course. The notes that follow are sufficient for the course though the recommended book will be of some help. A third supplementary evidence exercise will be set in association with these six lectures, and they should be handed in by friday, 8th March.

Lecture 1 (16th January):

Prolog:

What is AI? Characteristics of traditional AI Languages. Programs as Data. Prolog: its syntax; pattern matching; and control. Designing and coding Prolog programs; Prolog programming style.

Lecture 2 (19th January):

Prolog:

Prolog variables and unification. The list datastructure, recursion, Prolog search strategy, and backtracking.

Lecture 3 (23rd January):

Prolog:

Programming techniques, control of backtracking including the use of the cut, the use of negation

Lecture 4 (26th January):

Prolog:

Practical Prolog programming, programming tools, metalevel programming

Lecture 5 (30th January):

AI:

What is AI? Engineering smart systems. Understanding human intelligence. Exhaustive search: an illustration of depth-first and breadth-first search

Lecture 6 (2nd February):

AI:

Different approaches to exhaustive search: depth-first; breadth-first and iterative deepening.

Lecture 7 (6th February):

AI:

Simple two player games: the minimax approach

Lecture 8 (9th February):

AI:

Planning

Lecture 9 (13th February):

AI:

Intelligence involves Knowledge Representation, Pattern Matching and Search? Using analogical reasoning. Evans approach to analogy introduced (and finished in the next lecture).

Lecture 10 (16th February):

AI:

(Evans approach to analogy concluded.) Question Answering Systems. Some recent trends