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    An introduction to modern AI representation systems and problem-solving techniques.

    About this paper

    Paper title Artificial Intelligence
    Subject Computer Science
    EFTS 0.15
    Points 18 points
    Teaching period Semester 2 (On campus)
    Domestic Tuition Fees ( NZD ) $1,173.30
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    COSC 201 or COSC 242
    Recommended Preparation
    COSC 202
    Schedule C
    Arts and Music, Science

    Computer Science Adviser

    Teaching staff
    Lecturer: Dr Lech Szymanski
    Paper Structure

    In this paper we will look at some different definitions of intelligence and at the concept of intelligent agents, concentrating on the issue of how to get information about the world and how to make use of it. We will consider techniques for machine learning and probabilistic reasoning. Almost every human ability results from learning from experience: we will look at how these learning processes can be modelled computationally.

    Topics to be considered include:

    • Search and optimisation algorithms (including genetic algorithms)
    • Probabilistic reasoning method (including Bayesian methods)
    • Machine learning algorithms (with a focus on neural networks)
    Teaching Arrangements

    There are two 1-hour lectures, and one 2-hour lab session per week.


    Artificial Intelligence A Modern Approach (Fourth Edition), by Stuart Russell and Peter Norvig, Pearson 2020.

    Course outline
    View the course outline for COSC 343
    Graduate Attributes Emphasised
    Interdisciplinary perspective, Scholarship, Communication, Ethics, Teamwork.
    View more information about Otago's graduate attributes.
    Learning Outcomes

    Students who successfully complete this paper will gain an understanding of a selection of core concepts in AI research: autonomous agents, planning and search, probabilistic reasoning, machine learning, decision trees, neural networks and sequential decisions.

    • In each case, this understanding will be strengthened through practical exercises and experience with implemented systems
    • The paper will also give students an awareness of the increasing influence of these technologies in daily life


    Semester 2

    Teaching method
    This paper is taught On Campus
    Learning management system

    Computer Lab

    Stream Days Times Weeks
    Attend one stream from
    A1 Wednesday 14:00-15:50 29-35, 37-42
    A2 Wednesday 16:00-17:50 29-35, 37-42


    Stream Days Times Weeks
    A1 Monday 09:00-09:50 29-35, 37-42
    Wednesday 09:00-09:50 29-35, 37-42
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