Note: This is an archived Handbook entry from 2012.
|Dates & Locations:|| |
This subject is not offered in 2012.
|Time Commitment:||Contact Hours: 24 one-hour lectures (two per week) and 12 two-hour workshops (one per week) |
Total Time Commitment:
One of the following
Study Period Commencement:
Not offered in 2012
Semester 1, Semester 2
433-253 Algorithms and Data Structures
433 298 Algorithms and Data Structures
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:|| |
433-303 Artificial Intelligence
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
Associate Professor Tim Baldwin
Artificial intelligence is the quest to create intelligent agents that can complete complex tasks which are at present only achievable by humans. This broad field covers logic, probability, perception, reasoning, learning and action; and everything from Mars Rover robotic explorers to the Watson Jeopardy playing program. You will explore some of the vast area of artificial intelligence. Topics covered include: searching, problem solving, logic and deduction, knowledge representation, machine learning, and programming languages for artificial intelligence. Topics may also include some of the following: game playing, expert systems, pattern recognition, machine vision, natural language, robotics and planning, neural networks.
On completion of this subject, students should be able to:
To pass the subject, students must obtain at least 50% overall
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subject students should have developed the following generic skills:
Computing and Software Systems |
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