Course Outline


COMP3620/6320 is organized in 3 main topics:

1 Search Feb 23 โ€“ Mar 17/2021
2 Knowledge Repr. and Reasoning (KRR) Mar 23 โ€“ Apr 21/2021
3 Planning Apr 27 โ€“ May 12/2021

Each topic is 6 lectures long (3 weeks long except by the KRR because of the teaching break).

In addition to the 3 main topics, there is an introduction to AI in the first week and 2 guest lectures in the end of the semester (speakers to be defined).

The deliverables for COMP3620/6320 are:

  • 4 assignments (a warm-up assignment + one per topic)
  • 6 quizzes (2 per topic)
  • final exam (all assessable material)

For more information regarding the deliverables, late/extension policies, final marks and grades, see the course policies

Each topic is also accompanied by 2 tutorials and 2 lab sessions. For the:

  • Tutorials
    • The goal is to help understand the material and prepare exam.
    • We will discuss a list of questions and you have to try answering them before the tutorial.
    • There is a quiz in the end of each tutorial to provide a reality check (that is, check if you are really understanding the material so far).
  • Labs
    • The labs are unstructured (i.e., there is no lab/question sheet) and self-guided (i.e., you need to bring questions).
    • The goal is to get help from the tutors with the assignments
    • You have to get started well in advance with the assignments to make the most of the opportunity

In addition to tutorials and labs for each topic, there is an extra lab for the warm-up assignment.


Course Book: (recommended):

    Artificial Intelligence, A Modern Approach
    S. Russel and P. Norvig, Prentice Hall, 2010

Others (available on-line for free inside ANU network):

    A Concise Introduction to Models and Methods for Automated Planning
    B. Bonet and H. Geffner, Morgan & Claypool, 2013

Contact & Information

See the communication policy

Updated:    16 Feb 2021 / Responsible Officer:    Head of School / Page Contact:    Felipe Trevizan