Monash University Computing & Information Technology handbook 1995

Copyright © Monash University 1995
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CSC3091

Artificial intelligence

4 points * Two 1-hour lectures per week * First semester * Clayton * Prerequisites: As for CSC3010; additional prerequisite CSC2030 * Corequisites: As for CSC3030 * Prohibitions: RDT2821, RDT3501, RDT3691

This subject focuses on classic problems dealt with in the area of artificial intelligence, and commonly used solution techniques. The subject covers three topics. (i) Problem solving: general problem-solving techniques, such as backtracking and graph searching; game-playing methods, such as min-max and alpha-beta pruning; and planning techniques. (ii) Knowledge representation: different techniques to store and represent world knowledge, eg predicate calculus, conceptual dependency, frames, semantic nets. (iii) Natural language understanding.

Assessment

Examinations: 2 hours * Programming assignment

Recommended texts

Charniak E and McDermott D Introduction to artificial intelligence Addison-Wesley, 1985

Hasemer T Looking at Lisp Addison-Wesley, 1985

Nilsson N Principles of artificial intelligence Tioga Press, 1980

Rich E and Knight K Artificial intelligence 2nd edn, McGraw- Hill, 1991

Wilensky R Lispcraft Norton, 1984


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