COMP307 (2019) - Introduction to Artificial Intelligence


This course considers ideas and techniques from Artificial Intelligence. It first introduces a range of search algorithms that are used throughout AI. It then examines applications and techniques of AI, including rule-based systems for embodying human expertise, algorithms for planning and problem solving, natural language processing, methods for machine learning, and neural nets and other computation intelligence techniques.

Course learning objectives

Students who pass this course should be able to:

  1. Understand fundamental concepts and techniques of artificial intelligence, in areas such as search, machine learning, evolutionary computing, reasoning under uncertainty, rule based systems, and planning. (BE 3(a), 3(c), 3(d), 3(e)); (BSc COMP 1, 2, 3, 4).
  2. Apply these concepts and techniques to specific problems (including engineering applications). (BE 3(a), 3(c), 3(d), 3(e), 3(f)); (BSc COMP 1, 2, 3, 4).

Course content

Artificial Intelligence (AI) is intelligence exhibited by machines. Examples include self-driving cars, automatically planning a holiday, generating sensible conversation, learning to predict fog at Wellington Airport, reading a web page to get the answer to a question, recognising handwritten digits, detecting identity by checking fingerprints, detecting network intrusions, controlling robot actuators, processing and recognising images and signals, discovering and detecting the mathematical or logical relationship between output variables and a large number of inputs in economic and engineering tasks, or optimising parameter values in complex engineering problems. COMP 307 is an introduction to the ideas and techniques that computer scientists have developed to address these kinds of tasks.
The lectures cover following main topics: search techniques, machine learning including basic learning concepts and algorithms, neural networks and evolutionary learning, reasoning under uncertainty, planning and scheduling, knowledge based systems and AI Philosophy. The course includes a substantial amount of programming. The course will cover both science and engineering applications.

Withdrawal from Course

Withdrawal dates and process:


Mengjie Zhang (Coordinator)

Dr Qi Chen may give some guest lectures..

Teaching Format

During the trimester there will be typically two lectures and one tutorial per week.

Student feedback

Student feedback on University courses may be found at:

Dates (trimester, teaching & break dates)

  • Teaching: 04 March 2019 - 09 June 2019
  • Break: 15 April 2019 - 28 April 2019
  • Study period: 10 June 2019 - 13 June 2019
  • Exam period: 14 June 2019 - 29 June 2019

Class Times and Room Numbers

04 March 2019 - 14 April 2019

  • Tuesday 12:00 - 12:50 – LT205, Hugh Mackenzie, Kelburn
  • Wednesday 12:00 - 12:50 – LT205, Hugh Mackenzie, Kelburn
  • Friday 12:00 - 12:50 – LT205, Hugh Mackenzie, Kelburn
29 April 2019 - 09 June 2019

  • Tuesday 12:00 - 12:50 – LT205, Hugh Mackenzie, Kelburn
  • Wednesday 12:00 - 12:50 – LT1, Te Toki a Rata, Kelburn
  • Friday 12:00 - 12:50 – LT205, Hugh Mackenzie, Kelburn

Other Classes

There will be some scheduled helpdesks.


The textbook for COMP 307 is: Stuart J. Russell and Peter Norvig, Artificial Intelligence. A Modern Approach, Prentice-Hall, NJ, 3rd edition, 2009. Some online materials are available on the course website.

A Reading List is available via the course website.

  • Please see Talis.

Mandatory Course Requirements

In addition to achieving an overall pass mark of at least 50%, students must:

  • submit reasonable attempts for at least three of the four assignments.

If you believe that exceptional circumstances may prevent you from meeting the mandatory course requirements, contact the Course Coordinator for advice as soon as possible.


This course will be assessed through assignments and final examination. There will be four assignments. The first three assignments will involve a combination of programming and discussion; the final assignment does not have programming work.
The marks and feedback will be returned in two weeks after the submission of each assignment.

Assessment ItemDue Date or Test DateCLO(s)Percentage
Assignment 1 (3-4 weeks)Week 5CLO: 1,215%
Assignment 2 (3 weeks)Week 8CLO: 1,212%
Assignment 3 (2-3 weeks)Week 10CLO: 1,210%
Assignment 4 (2 weeks)Week 12CLO: 1,28%
Final Exam (2 hours)Exam PeriodCLO: 1,255%


The penalty for assignments that are handed in late without prior arrangement is one grade reduction per day. Assignments that are more than one week late will not be marked.


Individual extensions will only be granted in exceptional personal circumstances, and should be negotiated with the course coordinator before the deadline whenever possible. Documentation (eg, medical certificate) may be required.

Submission & Return

All work should be submitted through the ECS submission system, accessible through the course web pages. Marks and comments will be returned through the ECS marking system, also available through the course web pages.


In order to maintain satisfactory progress in COMP 307, you should plan to spend an average of 10 hours per week on this course. A plausible and approximate breakdown for these hours would be:

  • Lectures and tutorials: 3 hours
  • Readings, revision/review, and assignments: 7 hours

If assignments are left until the last minute, the amount of work spent in particular weeks may vary greatly.

Teaching Plan

Lecture schedules can be seen from the course website. See

Communication of Additional Information

1. Course website:
2. Course forum
3. Email sent by the lecturers to students at their ecs email addresses.

Offering CRN: 968

Points: 15
Prerequisites: COMP 261 or NWEN 241 or SWEN 221; ENGR 123 or MATH 151 or 161
Duration: 04 March 2019 - 30 June 2019
Starts: Trimester 1
Campus: Kelburn