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DD2438 Artificial Intelligence and Multi Agent Systems 15.0 credits

In this course, we will study problems related to

  • AI for computer games (such as Call of Duty, FIFA, Rocket League)
  • AI for robotics (such as multi robot search and rescue, robot soccer, 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 the simulation environment Unity 3D, 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.

Choose semester and course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.


For course offering

Spring 2025 agent25 programme students

Application code


Headings with content from the Course syllabus DD2438 (Autumn 2021–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

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.

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.

Literature and preparations

Specific prerequisites

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)


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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F


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

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Computer Science and Engineering, Information Technology, Information and Communication Technology

Education cycle

Second cycle

Add-on studies

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Petter Ögren,, telefon: 790 6646

Supplementary information

In this course, the EECS code of honor applies, see: