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CSE 460 ARTIFICIAL INTELLIGENCE
Instructor: Tunga Güngör (e-mail: [email protected])
Text Book: Prolog Programming for Artificial Intelligence (3rd edition)
Ivan Bratko, Addison Wesley, 2001
Reference Books and Periodicals:
AI Theory:
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Artificial Intelligence: A New Synthesis, Nils J.Nilsson, Morgan Kaufmann, 1998
The Essence of Artificial Intelligence, Alison Cawsey, Prentice Hall, 1998
Artificial Intelligence: Structures and Strategies for Complex Problem Solving (3rd edition),
George F.Luger, William A.Stubblefield, Addison-Wesley, 1998
Artificial Intelligence: A Modern Approach, Stuart Russell, Peter Norvig, Prentice Hall,
1995
Artificial Intelligence: Theory and Practice, Thomas Dean, James Allen, Yiannis
Aloimonos, Addison-Wesley, 1995
Philosophy and Artificial Intelligence, Todd C.Moody, Prentice Hall, 1993
Artificial Intelligence (2nd edition), Elaine Rich, Kevin Knight, McGraw-Hill, 1992
Introduction to Artificial Intelligence, Eugene Charniak, Drew McDermott, AddisonWesley, 1985
The Mind and the Machine: Philosophical Aspects of Artificial Intelligence, S.B.Torrance
(ed.), Ellis Horwood, 1984
Principles of Artificial Intelligence, Nils J.Nilsson, Springer-Verlag, 1980
AI Applications:
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Innovative Applications of Artificial Intelligence, Herbert Schorr, Alain Rappaport (ed.),
AAAI Press and MIT Press, 1989
A Guide to Commercial Artificial Intelligence: Fundamentals and Real-World Applications,
Wendy B.Rauch-Hindin, Prentice Hall, 1988
Artificial Intelligence: An Applications-oriented Approach, Daniel Schutzer, Van Nostrand
Reinhold Com., 1987
Periodicals:
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Artificial Intelligence, North-Holland Pub.
Lecture Hours:
Tuesday 10:00-13:00
Course Schedule:
Introduction
Basics of Prolog
Declarative vs. procedural programming
Facts, rules, and goals; clauses and procedures
Instantiation and unification; matching
Lists and operations on lists
Arithmetic in Prolog
Data abstraction
Backtracking
Cut, fail, and not
Closed-world assumption
Operating with files
Built-in predicates
Asserting and retracting clauses
Sorting and searching
Tree and graph representations
Depth-first vs. breadth-first search
Iterative deepening
Heuristics
Best-first search
A* algorithm
AND/OR graphs
Knowledge representation; semantic networks and
frames
Rule-based systems and expert systems
Learning strategies; induction and abduction
Game playing
Minimax principle; alpha-beta algorithm
Evaluation: (subject to change)
Midterm: % 30
Project: % 30
Final:
% 40
Notes:
 There will be a programming project in Prolog.
 The midterm and final examinations will be “closed books and notes”.
 You can obtain some of the reference books from the instructor.
 You can follow the announcements from the course web site.
 Attendance for lectures is not obligatory. But you are responsible from lectures’ contents.