COMPSCI 367 : Artificial Intelligence


2020 Semester Two (1205) (15 POINTS)

Course Prescription

The cornerstones of AI: representation, utilisation, and acquisition of knowledge. Taking a real world problem and representing it in a computer so that the computer can do inference. Utilising this knowledge and acquiring new knowledge is done by search which is the main technique behind planning and machine learning.

Course Overview

In  this  course,  you  will  cover  the  representation and utilisation of  knowledge.  These  are  the cornerstones  of  AI. You will investigate how  to take a  real  world  problem  and  represent  it  in  a computer, so that the computer can solve that problem. Utilising this knowledge is done by search. The basics of search and its use in problem solving will be covered. 
This course is good preparation for anyone wanting to do postgraduate study in Artificial Intelligence, e.g., compsci 765 or 767.
Note: The machine learning material has been removed from this course and is now a course of its own - compsci 361.

Course Requirements

Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255 Restriction: COMPSCI 761

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Represent in a declarative way, what it means for something to be a solution to a given problem. (Capability 1)
  2. Implement the main heuristic-search-based approaches to problem solving and their pro's and con's. (Capability 1)
  3. Elicit knowledge and represent it in intermediate knowledge representations. (Capability 1)
  4. Explain the differences between data driven and goal driven inference and can program a declarative rule-based system. (Capability 3)
  5. Represent knowledge in predicate calculus and prolog formats. (Capability 2)


Assessment Type Percentage Classification
Assignments 30% Individual Coursework
Test 10% Individual Test
Final Exam 60% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Final Exam
You have to pass both the theory [the exam and test] and the practical [i.e., assignments] components to pass this course.

Key Topics

History of AI
Knowledge Representation
Constraint Satisfaction
Natural Language Processing

Learning Resources

Artificial Intelligence: A Modern Approach by Stuart J. Russell, Peter Norvig, 3rd Ed.

Special Requirements


Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, on average, each week you can expect  3 hours of lectures, a 1 hour tutorial, 1 hour of reading and thinking about the content and 5 hours of work on assignments and/or test preparation.

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.


The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page:

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (


Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 27/07/2020 03:42 p.m.