Course Title: Games and Artificial Intelligence Techniques

Part A: Course Overview

Course Title: Games and Artificial Intelligence Techniques

Credit Points: 12.00

Terms

Course Code	Campus	Career	School	Learning Mode	Teaching Period(s)
COSC2527	City Campus	Undergraduate	140H Computer Science & Information Technology	Face-to-Face	Sem 2 2011, Sem 2 2012, Sem 1 2013, Sem 2 2014, Sem 2 2015
COSC2527	City Campus	Undergraduate	171H School of Science	Face-to-Face	Sem 1 2018, Sem 2 2019, Sem 2 2020, Sem 1 2021
COSC2527	City Campus	Undergraduate	175H Computing Technologies	Face-to-Face	Sem 1 2022, Sem 1 2023
COSC2528	City Campus	Postgraduate	140H Computer Science & Information Technology	Face-to-Face	Sem 2 2011, Sem 1 2013, Sem 2 2014, Sem 2 2015
COSC2528	City Campus	Postgraduate	171H School of Science	Face-to-Face	Sem 1 2018, Sem 2 2019, Sem 2 2020, Sem 1 2021
COSC2528	City Campus	Postgraduate	175H Computing Technologies	Face-to-Face	Sem 1 2022, Sem 1 2023

Course Coordinator: Dr. Michael Dann

Course Coordinator Phone: +61 3 9925 8963

Course Coordinator Email: michael.dann@rmit.edu.au

Course Coordinator Location: 14.08.07B

Pre-requisite Courses and Assumed Knowledge and Capabilities

Enforced Pre-requisite courses

Successful completion of:

COSC2123/COSC1285/COSC2469/COSC2203 - Algorithms and Analysis (Course ID 004302)
OR
COSC1295 - Advanced Programming (Course ID 004316)
OR
COSC1076/COSC2082 - Advanced Programming Techniques (Course ID 004068)
OR
COSC2391/COSC2440 - Further Programming (Course ID 014052)
OR
COSC2802 - Programming Bootcamp 2 (Course ID 054080)
OR
COSC2800 - IT Studio 2 (Course ID 054075)
OR
COSC3056 - Programming Studio 1 (Course ID 054081)

Note: it is a condition of enrolment at RMIT that you accept responsibility for ensuring that you have completed the prerequisite/s and agree to concurrently enrol in co-requisite courses before enrolling in a course.

For your information go to RMIT Course Requisites webpage.

Course Description

This course is an advanced seminar-style course involving a substantial practical component, developing a Computer Game incorporating Artificial Intelligence Techniques. Students will be guided through readings and subject content each week by the course leader(s). Topics include both theoretical topics in selected artificial intelligence techniques pertinent to game implementation, as well as practical tools implementing those techniques. Students will use such tools and techniques to build a specified interactive game over the course of the semester, incorporating intelligent behaviours into the game. This course involves a lot of self-learning and hence it suited to more advanced students.

Objectives/Learning Outcomes/Capability Development

1. Apply various AI techniques and tools in the context of games programming;
2. Design and develop a gaming application, based on existing games engines or platforms;
3. Contribute effectively in a team environment to develop a complex software system.

On successful completion of this course, you should be able to:

1. Demonstrate an understanding of various AI techniques and tools and how they are applied in the context of games programming;
2. Design and develop a gaming application, based on existing games engines or platforms;
3. Work effectively in a team environment to develop a complex software system.

Overview of Learning Activities

The learning activities included in this course are:

• classes run by academic staff, to introduce you to the key concepts and tools required for successful completion of the programming project;
• tutorials and/or labs and/or group discussions (including face-to-face and online forums) focused on projects and problem solving, providing feedback on progress and understanding, and used to discuss technical issues;
• regular consultation with an assigned project supervisor (i.e. a staff member), providing guidance with learning activities, feedback on progress, and help with resolving any issues;
• assignment deliverables, as described in Overview of Assessment and Assessment Tasks, designed to develop and demonstrate the practical aspects of the learning outcomes;
• private and group study, for working through readings and gaining practice at solving conceptual and technical problems.

Overview of Learning Resources

The course is supported by the Canvas learning management system which provides specific learning resources.

Prescribed Texts
Artificial Intelligence for Games - 2nd edition, Ian Millington & John
Funge, Morgan-Kauffman (2009)
978-012374731

References
AI Game Programming Wisdom 1-2-3-4, Steve Rabin ed., Charles River
Media (2002-2003-2006-2008)
AI Game Engine Programming, Brian Schwab, Charles River Media (2008)
Programming Game AI by Example, Mat Buckland, Charles River Media
(2008)
Artificial Intelligence: A Modern Approach - 2nd or 3rd edition, Stuart Russell and Peter Norvig, Prentice Hall (2002 or 2009)

Overview of Assessment

The course involves a substantial practical programming assignment, involving game-programming platforms and integration of tools implementing artificial intelligence techniques. The programming assignment will be performed in teams; students will be required to submit a breakdown of work tasks carried out by each team member for all assignment work.

Assessment Tasks

Assessment 1: Programming assignment (team)
Weighting: 40%
This assessment task supports CLOs : 1-3

Assessment 2: Programming assignment (team)
Weighting: 20%
This assessment task supports CLOs : 1-3

Assessment 3: Programming assignment (individual)
Weighting: 40%
This assessment task supports CLOs : 1 and 2

If you have a long term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.