Computer Science, Prifysgol Cymru Aberystwyth University of Wales
CS26210 (1995-96 session)
Artificial Intelligence Concepts
Brief 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 introduces students to the fundamental concepts of AI. Key
issues including knowledge representation and reasoning, expert
systems and learning are addressed both theoretically and
practically.
Aims, Objectives, Syllabus, Booklist
Further Details
- Number of lectures
- 12
- Number of seminars/tutorials
- 12
- Number of practicals
- 0
- Coordinator
- Dr. Fred Long
- Other staff involved
- Not yet known
- Pre-requisites
- Pass or exemption in Computer Science at Part I or CS10310
by arrangement with the department
- Co-requisites
- None
- Incompatibilities
-
CS36210
- Assessment
- Assessed coursework - 40%
Written exam -
60%
- Timing
- This module is offered only in Semester 2
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 and reasoning, expert systems and learning.
Students will be required to implement these concepts using an
Artificial Intelligence programming language.
Objectives
On successful completion of this module students should:
-
understand the importance of knowledge representation and
their role in Artificial Intelligence systems;
-
understand the use search in the solution of problems such
as path planning and game playing;
-
be familiar with the principle techniques used in
implementing machine learning;
-
understand the fundamentals of first generation expert
system technology, and the conceptual basis of current
attempts to overcome its limitations;
-
be capable of implementing fundamental Artificial
Intelligence algorithms in the Artificial Intelligence
language Lisp.
Syllabus
-
Introduction - 1 Lecture
-
The origins of Artificial Intelligence; 4 definitions
of Artificial Intelligence. Characterising good and bad problem
domains.
-
Search - 2 Lectures
-
The role of search in Artificial Intelligence. Search
strategies: basic search; heuristic search; and game playing.
Two workshops implementing depth- and breadth-first search,
heuristic search and search space pruning.
-
Knowledge Representation and Inference - 3 Lectures
-
Issues in knowledge representation: representation
adequacy; inferential adequacy; inferential efficiency;
acquisitional efficiency. Knowledge Representation formalisms:
propositional and predicate logic, procedural representations;
semantic nets; frame-based representations.
-
Genetic Algorithms - 1 Lecture
-
Chromosomes and hereditary traits; survival of the
fittest; crossover; the rank method.
-
Expert Systems - 2 Lectures
-
Characterising first generation expert systems.
Expert system structure: knowledge representation; control
strategies. Limitations of current expert system technology.
-
Learning - 3 Lectures
-
The role of learning in Artificial Intelligence.
Symbollic approaches to learning: rote learning; Winston's arch
learning program; version spaces and CYC.
-
Lisp - 12 Practicals
-
Workshops on programming in Lisp.
Booklist
It is considered essential to purchase the following
-
E. Rich and K. Knight.
Artificial Intelligence.
McGraw Hill, 2nd. edition, 1991.
Students are likely to need ready access to the following
-
Robert Wilensky.
Common LISPcraft.
W.W. Norton, New York, 1986.
-
Charniak and McDermott.
Introduction to Artificial Intelligence.
Addison Wesley, 1985.
-
P. H. Winston.
Artificial Intelligence.
Addison Wesley, 3rd. edition, 1992.
The following should be consulted for different approaches or for further information
-
S. C. Shapiro.
Encyclopedia of Artificial Intelligence.
Addison-Wesley, 1992.
Version 4.1
Syllabus
John Hunt Departmental Advisor
jjh@aber.ac.uk
Dept of Computer Science, UW Aberystwyth (disclaimer)