module specification

CU6052 - Artificial Intelligence for Games (2019/20)

Module specification Module approved to run in 2019/20
Module title Artificial Intelligence for Games
Module level Honours (06)
Credit rating for module 15
School School of Computing and Digital Media
Total study hours 150
 
45 hours Scheduled learning & teaching activities
105 hours Guided independent study
Assessment components
Type Weighting Qualifying mark Description
Coursework 25%   Research document, 2000 words
Coursework 75%   Implementation of prototype game + technical documentation
Running in 2019/20
Period Campus Day Time Module Leader
Spring semester North Thursday Afternoon

Module summary

This module looks at the use of AI in the development of computer games, digital media and other products from a variety of perspectives.  Students will undertake a small piece of research in this field and present their findings.   This work will underpin a prototype, built using industry-standard tools and including a system model representation and a description of the final product.

This module is designed to further develop programming and game design and development skills.  The module aims to:

· develop students' awareness of artificial intelligence and its current and potential
       applications in the field of computer games, digital media and product design
-     enable students to solve problems in designing and building complex game
      artefacts;
· implement the production of complex game systems;
· develop communication skills with particular reference to artificial intelligence;
-     develop research and presentation skills;
      · equip students for employment in the games industry

Prior learning requirements

CU6051 Artificial Intelligence

Syllabus

Practical application of AI in a games development IDE
-     pathway finding algorithms LO1, 2, 3
-     state machines;
-     steering behaviours;
-     approaches to agent design;
-     design techniques
-     game publication pipeline LO4

Balance of independent study and scheduled teaching activity

A problem based learning approach will be used in the module delivery. 

Scheduled teaching accounts for approximately one third of module time; independent study accounts for two thirds.  Students have access to VLE and external resources such as videos, guest lecturers.  The output is designed [1] to encourage reflection and promote research skills; [2] to be part of a portfolio of specialised AI work.

Learning outcomes

On successful completion of this module, students will be able to:

LO1  understand the application of Artificial Intelligence to the field of computer
                  games;
LO2 be able to apply theoretical understanding in practical scenarios and be
                  competent at solving interaction design problems;
LO3 undertake research and present findings;
LO4           understand process involved in taking prototype to market.

Assessment strategy

Without being prescriptive the following is indicative of the assessment strategy. It is likely that practical course work will begin in the first third of the module and completed by towards the end of the module. The work will implement ideas that have been introduced in lectures to assure the student has understood what has been presented. The module is passed on the aggregate mark.

There is regular formative assessment to encourage students, maintain progress and offer opportunities for peer review and self-direction.

Bibliography

Textbooks
Aversa (2018) Unity Artificial Intelligence Programming: Add powerful, believable, and fun AI  entities in your game with the power of Unity 4th Edition; Packt Publishing
ISBN-10: 1789533910

Websites:
http://www.gameprogrammingpatterns.com/
https://www.redblobgames.com/
https://gamedevelopment.tutsplus.com/series/understanding-steering-behaviors--gamedev-12732