- Code COMP4620
- Unit Value 6 units
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:
- 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).
Professional Skills Mapping:
- Assignments (45) [LO null]
- Seminar (15) [LO null]
- Final Exam (40) [LO null]
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Workload30 one hour lectures
Requisite and Incompatibility
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.
Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found 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
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|
|5909||25 Jul 2022||01 Aug 2022||31 Aug 2022||28 Oct 2022||In Person||N/A|