Artificial intelligence
4 points
* Two 1-hour lectures per week
* Second semester
* Clayton
* Prerequisites: CSC2030, CSC2040 and either CSC2940 or
CSC3940
* Prohibitions: CSC2091, GCO3815, RDT3691
Objectives On completion of the subject, students should have a working knowledge of basic search techniques, knowledge representation and reasoning mechanisms, and planning systems; be able to analyse problems and determine which artificial intelligence techniques are applicable.
Synopsis Topics include history and philosophy of artificial intelligence; problem solving and search (heuristic search, iterative improvement, game playing); knowledge representation and reasoning (extension of material on propositional and first-order logic for artificial intelligence applications, situation calculus, planning, frames and semantic networks); expert systems overview (production systems, certainty factors); machine learning (decision trees, neural networks, genetic algorithms).
Assessment: Examination (2 hours): 70%
* Assignments: 30%
Recommended texts
Russell S and Norvig P Artificial intelligence: A modern approach Prentice-Hall, 1994
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