This is an advanced undergraduate course that covers advanced topics in Artificial Intelligence. Topics vary from one offering to the next and are likely to be drawn from the following list: planning, scheduling, games, search, reasoning (constraint-based, model-based, spatial, temporal), knowledge representation, decision-making under uncertainty, reinforcement learning, agents, foundations.
Upon successful completion, students will have the knowledge and skills to:
The content of the course will vary at each offering. In general, through this course, students should...
- Gain both a wide and a deep knowledge of the topic(s) taught in the current instance of the course.
- Improve their skills at navigating through, and critically examining, the scientific literature on the taught topic(s).
Assignments (45%); Seminar (15%); Final Exam (40%)
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Workload30 one hour lectures
Requisite and Incompatibility
Marcus Hutter (2005) Universal Artificial Intelligence, EATCS, Springer.
Shane Legg (2008) Machine Super Intelligence, Lulu, PhD thesis
Students are assumed to have solid background knowledge in general computer science (e.g., programming experience; some basic theoretical CS), but no specialist knowledge.
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:
- 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.
Offerings, Dates and Class Summary Links
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.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|9207||22 Jul 2019||29 Jul 2019||31 Aug 2019||25 Oct 2019||In Person||N/A|