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.

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Offering and execution

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Course information

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.

Course Disposition

No information inserted

Literature and preparations

Specific prerequisites *

KTH-students:
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)

Equipment

No information inserted

Literature

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

Examination and completion

Grading scale *

P, F

Examination *

  • 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.

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.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Petter Ögren

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web DD2438

Offered by

EECS/Intelligent Systems

Main field of study *

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

Education cycle *

Second cycle

Add-on studies

No information inserted

Contact

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

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.

Supplementary information

In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex