• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Classification Advanced
  • Course subject Computer Science
  • Areas of interest Computer Science, Information Technology, Intelligent Systems, Artifical Intelligence
  • Academic career PGRD
  • Course convener
    • Dr Felipe Trevizan
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in First Semester 2020
    See Future Offerings

Artificial intelligence is the science that studies and develops methods of making computers more /intelligent/. The focus of this course is on core AI techniques for search, knowledge representation and reasoning, planning, and designing intelligent agents. The course also aims to give an overview of the historical, philosophical, and logical foundations of AI.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

After completing this course, students should be able to:
  1. Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem.
  2. Formalise a given problem in the language/framework of different AI methods (e.g., as a search problem, as a constraint satisfaction problem, as a planning problem, etc).
  3. Implement basic AI algorithms (e.g., standard search or constraint propagation algorithms).
  4. Design and perform an empirical evaluation of different algorithms on a problem formalisation, and state the conclusions that the evaluation supports.

Other Information

http://cs.anu.edu.au/student/comp3620/

Indicative Assessment

Assignments (50%), Final Examination (50%)

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Twenty-two one-hour lectures, six tutorials and four laboratory sessions.

Requisite and Incompatibility

To enrol in this course you must have completed COMP6710, and have completed or be currently enrolled in COMP6262. Incompatible with COMP3620.

Prescribed Texts

Stuart Russell and Peter Norvig (2010) Artificial Intelligence. A Modern Approach.

Specialisations

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
2208 24 Feb 2020 02 Mar 2020 31 Mar 2020 29 May 2020 In Person N/A

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