Artificial intelligence
Dr H Selvaraj
6 points * 4 hours per week * Second semester * Gippsland/Distance * Prerequisites: GCO1812 * Prohibitions: CSC3091, RDT3691
Objectives Students completing this subject should be able to explain the fundamental concepts of artificial intelligence; describe some AI techniques and applications; use Prolog to solve problems and build expert systems.
Synopsis Can machines think? the physical symbol system hypothesis; history of AI; the Turing test; languages of AI; the structure of Prolog; facts, rules, queries; instantiation and backtracking; list processing; depth-first and breadth-first searches; directed searches and the A* algorithm; knowledge representation; frames, scripts; expert systems; learning; genetic algorithms; neural networks; backpropagation. Access to the university's computer systems via modem is compulsory for distance education students.
Assessment Examination (3 hours): 70% * Other assessment modes: 30%
Prescribed texts
Luger G F and Stubblefield W A Artificial intelligence: Structures and strategies for complex problem solving 2nd edn, Benjamin-Cummings, 1993
| Published by Monash University, Clayton, Victoria
3168 Copyright © Monash University 1996 - All Rights Reserved - Caution Authorised by the Academic Registrar December 1996 |