Official course description, subject to change:
Basic info last published 21/10-21

Foundations of Game AI

Course info
Language:
English
ECTS points:
7.5
Course code:
KGFOGAA1KU
Participants max:
50
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price (single subject):
10625 DKK
Programme
Level:
MSc. Master
Programme:
MSc in Games
Staff
Course manager
Associate Professor
Teacher
Full Professor
Course semester
Semester
Forår 2022
Start
31 January 2022
End
27 May 2022
Exam
Abstract

Through this course, the students will learn about the aspects of game programming commonly involving artificial intelligence methods, which methods are used and how to implement them.


Description

The course will go through a series of areas of application of artificial intelligence in games.

Each area will be discussed and formalised as an AI problem. For each of these problems, the students will learn one or multiple algorithms that are used as a solution in modern game development and how to implement them.

The main areas of game that will be covered are: input and output representation, pre-processing, path finding, NPC behaviour and procedural content generation.

Formal prerequisites

Students must have experience with and be comfortable with programming, and be capable of independently implementing algorithms from descriptions. This corresponds to at least having passed an introductory programming course, and preferably also an intermediate-level programming course. The course will contain compulsory programming.

Intended learning outcomes

After the course, the student should be able to:

  • Analyse a gameplay or game technology related problem in terms of an artificial intelligence problem
  • Given a formalised AI problem identify the correct solutions discussed in class.
  • Compare different AI solutions in terms of effectiveness and computational efficiency.
  • Describe and implement the algorithms discussed in class.
  • Combine multiple algorithms to create complex solutions (e.g. agent behaviours).
  • Given a new problem description within the context of Game AI, theorise a potential solution using the algorithms discussed in class.
Ordinary exam
Exam type:
B: Oral exam, External (7-point scale)
Exam variation:
B22: Oral exam with no time for preparation.