IA-2-014

• Information technology 2014 - Service oriented architectures and system design
• Information technology 2015 - Service oriented architectures and system design
• Information technology 2016 - Service oriented architectures and system design
• Information technology 2017 - Service oriented architectures and system design
• Information technology 2018 - Service oriented architectures and system design

1 (2018-08-01 to 2018-10-21)

Swedish

Compulsory

First

3

5 cr

The aim of the course is that the student learn to design and realize believable behavior and intelligence in autonomous (non-player) characters in 3D games. The student will gain knowledge in different techniques for artificial intelligence being popular in games. The course also includes a theoretical part on image process with the aim to provide the student knowledge in handling textures in games but also to provide an into to the computer vision course which will be held in period 3.

After completing the course, the student is expected to know and be able to apply popular techniques for artificial intelligence when creating believable behavior for non-player characters in 3D games. The student is also expected to gain basic knowledge in image processing.

students should be
able to understand how processes can be modeled
and described by equations. The student has a
solid foundation to build the process using an
object-oriented software design.

Game programming in Unity (C#)
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- Creating 3D game scenes and repetition of vectors
- Simple movements, e.g. moving an autonomous character towards a goal
- Moving autonomous characters according to waypoints
- Graph theory and path finding
- "NavMeshes"
- Finite state machines
- Behavior trees

Basics of Image Processing
--------------------------
- 2-dimensional sampling and quantising
- - Image and Planer spectrum
- - Sampling and Quantising
- Image manipulation
- - Brightness, Contrast and Gradation
- - Colour Hue and Saturation
- Image procesing with linear filters
- - Basics of FIR-filters
- - Effects of filters in Images
- Image processing with nonlinear filters
- - Adaptive filters (Sharpness enhancement, noise reduction)
- - Medianfilter

Earlier NoC-courses.

Tutorials and videos on the web are published during the course in Itslearning.

• Lectures - 40 hours
• Individual studies - 95 hours

• Total workload of the course: 135 hours
• Of which autonomous studies: 135 hours
• Of which scheduled studies: 0 hours

Participation in tuition

The course is assessed based on 4 programming projects on computer AI (max 85p) and a theoretical part on image processing (max 15 p). The projects must be handed in by 29.10 and be presented at 1 of 3 alternative project feedback sessions (please sign up at Itslearning). Projects handed in late are assessed but the course grade is decreased by 1 for each started weak past the deadline. The theoretical part is held by a guest lecturer and requires active participation in the lectures. At least 50p is required to pass the course.

Karlsson Jonny

Karlsson Jonny

https://arcada.itslearning.com/ External link

No limit (34 students enrolled)

12 months after course has ended

2018-08-13 to 2018-09-09

2018-10-29 - Other assignments