ABOUT THIS COURSE (MSc ARTIFICIAL INTELLIGENCE)

The Documantation Conatined with this course is a collection of handouts and associated material for a masters level course. The lecture material is given and was created by Dr W F B Jones. The material was transferred and arranged for HTML by Dr A D Marshall.

NOTE: Book Recommendations

This majority of this lecture course is based on Rich and Knight book "Artificial Intelligence". The notes here do not replace such a book and it is indeed recommended that these notes be used in conjunction with this book.

Note also that the third year course Artificial Intelligence II also recomends the Rich and Knight book.

A few sections therefore do closely follow that of Rich and Knights book.

Note: That other topics notably Lisp Programming and Game Playing are covered in much greater detail than the above the book. Therefore other Texts may need to be consulted in conjunction with these notes.

The Syllabus given below gives course contents details and does not necessarily follow the lecture course on a lecture buy lecture basis.

SYLLABUS FOR MSc ARTIFICIAL INTELLIGENCE

1 GENERAL INTRODUCTION; AI DEFINITIONS; A I TECHNIQUES;

SIMPLE GAME , TIC TAC TOE; QUESTION ANSWERING SYSTEMS; ALGORITHMS & DATA STRUCTURES; SAMPLE DIALOGUE SHOPPING; SUCCESS CRITERIA;

2 THE ELEMENTS AND CHARACTERISTICS OF THE LISP

PROGRAMMING LANGUAGE USING COMMON LISP ON MACS;

3 USER DEFINED FUNCTIONS IN LISP

4 RECURSIVE FUNCTIONS IN LISP

5 EXAMPLES OF THE USE OF LISP FUNCTIONS IN

ARTIFICIAL INTELLIGENCE

6 EXAMPLES OF SORTING AND SEARCHING

7 PATTERN MATCHING USING A DATABASE

8 THE DESIGN OF A SIMPLE PRODUCTION SYSTEM

9 PROBLEMS PROBLEM SPACES AND SYSTEMATIC SEARCHING;

CLASSICAL WATER JUG PROBLEM; PROBLEM CHARACTERISTICS;

10 SOLUTION CHARACTERISTICS; ISSUES IN THE DESIGN OF

SEARCH PROGRAMS; HEURISTIC SEARCH TECHNIQUES;

GENERATE & TEST; HILL CLIMBING;

11 METHOD OF STEEPEST ASCENT; SIMULATED ANNEALING;

BEST FIRST ; A* ALGORITHM

12 AGENDAS, AGENDA DRIVEN SEARCH; PROBLEM REDUCTION;

AND-OR GRAPHS; AO* ALGORITHM;

13 CONSTRAINT SATISFACTION , CRYPTARITHMETIC;

MEANS-END ANALYSIS, EXAMPLE AND ALGORITHM;

14 GAMES; TWO PERSON GAMES SAFE AND UNSAFE POSITIONS;

THREE VERSIONS OF NIM, GRUNDY'S GAME;

15 GAMES, THE THEORY OF GAMES, USE OF TREES, MINIMAXING

ALPHA BETA CUTOFFS;

16 GAMES, EXAMPLES SUCH AS TICTACTOE, KALAH, CHECKERS

ILLUSTRATING LOOKAHEAD AND LEARNING TECHNIQUES;

17 EARLY EFFORTS IN A I; SUCH AS BASEBALL, SADSAM, STUDENT;

18 NATURAL LANGUAGE PROCESSING; ENGLISH INPUT TEXT;

PARSING TECHNIQUES USING ATN'S AND RTN'S;

19 WINOGRAD'S SHRDLU; THE SIMULATION OF A BLOCK'S WORLD USING A STRUCTURED PROGRAM AND GRAPHICAL DISPLAY;

20 WASP --WAIT AND SEE PARSER;

AN INTERESTING APPROACH USING A STACK AND LOOKAHEAD;

WFBJ OCTOBER 1993