Handbook 1996 : Faculty of Engineering (Volume 4 page 106)
Computer Science subject : Next:433-313 | Prev:433-247 | Search | Help
433-303 "Artificial intelligence" appears differently in several places - choose the one you want:
1. Computer Science, Faculty of Engineering (v4, p106) : Next:433-313 | Prev:433-247
3. Geomatics, Faculty of Engineering (v4, p118) : Next:433-313 | Prev:433-244
Credit points: 12.5
Coordinator: Dr. L. Naish
Prerequisite: Computer Science 433-242, 433-243 and 433-244
Pre/Corequisite: Computer Science 433-241 or Electrical Engineering 431-204
Contact: 26 hours of lectures and approximately 17 hours of practice classes
Timetable: First semester
Objectives:
On successful completion of this subject students should:
- understand the foundations of Artificial Intelligence and the associated technologies that have evolved in both declarative and procedural approaches
- have attained basic proficiency skills in logic programming, and in carrying out algorithmic analyses of problems in a variety of relevant areas
Content:
Searching, problem solving, logic and deduction, knowledge representation, machine learning, programming languages for artificial intelligence. A selection from the following: game playing, expert systems, pattern recognition, machine vision, natural language, robotics and planning.
Assessment:
Up to three hours of written examinations at the end of the subject. Project work, which is expected to take about 36 hours, must be completed satisfactorily to pass the subject. Weighting of assessment components will be made known at the commencement of the subject.
1. Computer Science, Faculty of Engineering (v4, p106) : Next:433-313 | Prev:433-247
3. Geomatics, Faculty of Engineering (v4, p118) : Next:433-313 | Prev:433-244
2. Computer Science, Faculty of Science (v4, p182) : Next:433-313 | Prev:433-247
Credit points: 12.5
Coordinator: Dr L Naish.
Prerequisite: Computer Science 433-242, 433-243 and 433-244
Pre/Corequisite: Computer Science 433-241 or Electrical Engineering 431-204
Contact: 26 lectures and approximately 17 hours of practice classes
Timetable: First semester
Objectives:
On successful completion of this subject, students should:
- understand the foundations of Artificial Intelligence and the associated technologies that have evolved in both declarative and procedural approaches;
- have attained basic proficiency skills in logic programming, and in carrying out algorithmic analyses of problems in a variety of relevant areas.
Content:
Searching, problem solving, logic and deduction, knowledge representation, machine learning, programming languages for artificial intelligence. A selection from the following: game playing, expert systems, pattern recognition, machine vision, natural language, robotics, and planning.
Assessment:
Up to three hours of written examinations at the end of the subject. Project work, which is expected to take about 36 hours, must be completed satisfactorily to pass the subject. Weighting of assessment components will be made known at the commencement of the subject.
* Note that CONTACT, CONTENT, COORDINATOR, OBJECTIVES differs from the maintainer's version above. A log of variations is available.
2. Computer Science, Faculty of Science (v4, p182) : Next:433-313 | Prev:433-247
Status: Official 1996 Date created: Oct 9 1995 Last modified: Oct 9 1995 Authorised by: Academic Registrar Email enquiries: Course_Information@registrar.unimelb.edu.au
Maintained by: Dept. of Computer Science, Faculty of Engineering.
Copyright © University of Melbourne 1995,1996.