The course takes place in period

2 (2019-10-28 to 2019-12-31)

Level/category

Professional studies

Teaching language

Swedish

Type of course

Compulsory

Cycle/level of course

First

Recommended year of study

3

Total number of ECTS

5 cr

Competency aims

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.

Learning outcomes

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 environments. The student is
also expected to gain basic knowledge in image
processing.

Course contents

AI development in Unity and C#

  • Moving autonomous characters according to
    waypoints
  • "NavMeshes" for pathfinding
  • Finite state machines
  • Behavior trees
  • Goal Oriented Action Planning (GOAP)

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

Prerequisites and co-requisites

Earlier Unity courses:

  • vectors and forces
  • oscillation and particle systems

Recommended or required reading

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

Study activities

  • Lectures - 40 hours
  • Individual studies - 95 hours

Workload

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

Mode of Delivery

Participation in tuition

Assessment methods

Assessment requirements

  • 4 projects on AI in unity (max 100p)
  • Guestlectures on image processing (active
    participation gives 15 bonus points!)

The projects must be handed in on time and be
presented on 1 of 3 alternative project feedback
sessions (sing up to these on Itslearning).

A minimum of 50p is required for approved course.

Teacher

Karlsson Jonny

Examiner

Karlsson Jonny

Group size

No limit (30 students enrolled)

Assignments valid until

12 months after course has ended

Course enrolment period

2019-10-14 to 2019-11-10

Assessment methods

Date will be announced later - Other assignments

Room reservations
Date Time Room Title Description Organizer
2019-10-21 13:15 - 16:00 A503 Autonoma Agenter Buchwald Peter
2019-10-22 10:15 - 13:00 D4109 Autonoma Agenter Buchwald Peter
2019-10-24 13:15 - 16:00 A503 Autonoma Agenter Buchwald Peter
2019-10-29 12:15 - 16:00 E385 Autonoma Agenter Karlsson Jonny
2019-11-04 12:00 - 16:00 E385 Autonoma Agenter Karlsson Jonny
2019-11-12 09:00 - 11:00 F365 Autonoma Agenter Karlsson Jonny
2019-11-14 09:00 - 11:00 F365 Autonoma Agenter Karlsson Jonny
2019-11-21 09:15 - 12:00 E387 Autonoma Agenter Karlsson Jonny
2019-11-26 09:15 - 13:00 F365 Autonoma Agenter Karlsson Jonny
2019-12-05 09:15 - 13:00 F365 Autonoma Agenter Karlsson Jonny
2019-12-09 12:15 - 16:00 F365 Autonoma Agenter Karlsson Jonny
2019-12-16 12:15 - 16:00 F365 Autonoma Agenter Karlsson Jonny
2019-12-19 09:00 - 16:00 F365 Autonoma Agenter: Projektpresentation/-feedbacktillfälle 1 30min per student/arbetspar. Anmäl dej på Itslearning Karlsson Jonny
2020-01-29 09:00 - 13:00 D4103 Autonoma Agenter: Projektpresentation/-feedbacktillfälle 2 30min per student/arbetspar. Anmäl dej på Itslearning Karlsson Jonny

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