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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: 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: 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: 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.