DD2438 Artificial Intelligence and Multi Agent Systems 15.0 credits

Artificiell intelligens och multiagentsystem

In this course, we will study problems related to

  • AI for computer games (such as Call of Duty, FIFA14, Starcraft)
  • AI for multi robot search and rescue
  • AI for robot soccer
  • AI for domestic service robots

This includes topics such as

  • Cooperative path planning
  • Cooperative task assignment
  • Formation keeping
  • Motion coordination 

In computer games, as well as in future robot systems,groups of cooperative agents, so-called multi agent systems, bring new possibilities in terms of capabilities, efficiency and flexibility.

In this course you will design and implement a number of solutions to multi agent problems. You will be using simulation environments such as

  • Unity 3D (https://unity3d.com)
  • Unreal engine (https://www.unrealengine.com/)

That enable you to understand, test and develop you designs, in a polished environment, but also export them to stand alone games (if you want to).

The course will be given in English.

  • Education cycle

    Second cycle
  • Academic level (A-D)

  • Main field of study

    Computer Science and Engineering
    Information Technology
    Information and Communication Technology
  • Grading scale

    P, F

Course offerings

Spring 18 agent18 for programme students FULL

Spring 19 agent19 for programme students

Intended learning outcomes

After completing the course the students should:

  • be able to use a number of important tools and technologies used in artificial intelligence and multi agent systems
  • be able to develop intelligent multi-agent systems
  • be able to assess the value of, and to a suitable extent utilize, existing solutions as a part of a programming project
  • be able to plan and lead the work in a larger project
  • be able to present their work and results, both orally and in writing
  • be able to write a basic scientific paper in English.

Course main content

The students will in project form design and implement a multi-agent team performing a task. The actual course content can vary based on which solutions the students choose to use.
The following areas will to a smaller or greater extent, dependent on the students' choices, be treated in the course: 

  • Cooperative path planning
  • Cooperative task assignment
  • Formation keeping
  • Motion coordination 

The course will also train the ability to manage, plan and participate in larger projects,  assess existing solutions and their possible use, and work with existing code.



2D1345/DD1345, Introduction to Computer Science and 2D1240/DN1240, Numerical Methods, Basic Course II or 2D1241/DN1241 Numerical Methods, Basic Course III or equivalent.
2D1363/DD1363, Software Engineering or equivalent is recommended.

Single course students:
90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.

Recommended prerequisites

DD2380 Artificial Intelligence (or a similar course)


To be announced at least 4 weeks before course start at course web page.

Required equipment


  • INL1 - Hand-in Assignment, 3.0, grading scale: P, F
  • PRO1 - Software Engineering Project, 4.0, grading scale: P, F
  • PRO2 - Software Engineering Project, 4.0, grading scale: P, F
  • PRO3 - Software Engineering Project, 4.0, grading scale: P, F

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.

Requirements for final grade

Offered by

CSC/Robotics, Perception and Learning


Petter Ögren, petter@kth.se, telefon: 790 6646


Petter Ögren <petter@kth.se>


Course syllabus valid from: Spring 2014.
Examination information valid from: Spring 2014.