This is an advanced postgraduate course that offers students the opportunity to study a special thematic area within the discipline of Artificial Intelligence. The topics will vary from year to year in response to emerging theoretical and practical issues in the discipline, as well as the research interests and expertise of academics and sessional staff. They will be drawn from the broad areas of Artificial Intelligence, and could include (but not limited to) the following topics: Planning, Scheduling, Games, Search, Reasoning (constraint-based, model-based, spatial, temporal), Knowledge representation, Decision-making under uncertainty, Integrated planning and learning, Reinforcement learning, and Robotics.Please see the class website for the specific topics covered in a particular semester.
Additional source review: awaiting review. Published wording is shown below.
Some conditions may need additional evidence or clarification. These are prototype interpretations, not ANU decisions or degree-completion checks.
Requisite and Incompatibility
To enrol in this course you must have completed COMP6320 or COMP3620. Additional Prerequisite courses for the Advanced Topic will be listed on the SoCo website (Special Topics in Computing page ) when the course topic is announced. Students who meet the pre-requisites can request a permission code following the instructions for Enrolling in CSS courses . Incompatible with COMP4620.
You will need to contact the School of Computing to request a permission code to enrol in this course.
Referenced entries (3)
Links and code mentions retain their original context above. They may describe options, prerequisites or exclusions.
- COMP6320 · 2027
- COMP3620 · 2027 · saved source not linked
- COMP4620 · 2027 · saved source not linked
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Gain both a wide and a deep knowledge of the topic(s) taught in the current instance of the course.
Navigate through, and critically examine, the scientific literature on the taught topic(s).
Plan and execute project work and/or a piece of research and scholarship in the advanced topic(s)
Reflect on current approaches of the advanced topic(s) and evaluate their limitations
Published offerings
Future offerings are indicative. Only recognised 2027 sessions with a published class number are offered in the enrolment demo.
| Year | Session | Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|---|---|
| 2027 | Second Semester | 10077 | 26 Jul 2027 | 02 Aug 2027 | 31 Aug 2027 | 29 Oct 2027 | In Person | N/A |
| 2028 | Second Semester | 10839 | 24 Jul 2028 | 31 Jul 2028 | 31 Aug 2028 | 27 Oct 2028 | In Person | N/A |
Complete offering text
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. 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. 2027 2028 Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 10077 26 Jul 2027 02 Aug 2027 31 Aug 2027 29 Oct 2027 In Person N/A Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 10839 24 Jul 2028 31 Jul 2028 31 Aug 2028 27 Oct 2028 In Person N/A
Source evidence (2 saved copies)
Matching copies share this record. Their original file locations and checksums are retained.
assets/Courses/Artificial Intelligence/8000/Advanced Topics in Artificial intelligence/Advanced Topics in Artificial intelligence - ANU.html
Published ANU page · saved page URL
SHA-256: 3a88b3f750b7a37d2a4d6652e525b07126e496d325e4986e4f5ff84d94ca3a3eassets/Courses/Artificial Intelligence/8000/Advanced Topics in Machine Learning/Advanced Topics in Artificial intelligence - ANU.html
Published ANU page · saved page URL
SHA-256: 13e96469272b5d77d61cdad476e91b3adfec7f6bf1d3b40296775ea7107185da