Schedule, syllabus and examination date

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Course content

This course gives you an introduction to systems with multiple agents/units/robots that mutually depend on each other’s behaviors in order to evaluate own or collective system performance. The course will cover theory for strategic interaction between self-interested agents as well as more altruistic agents working explicitly together in complex distributed environments. Game theory and swarm intelligence will be central parts of the course curriculum.

As a PhD candidate you will be additionally be required to study the principles of evolutionary game theory and present this in a written report.

Learning outcome

The course gives you a comprehensive understanding of how to analyze, model and design complex multiagent systems. After completing the course you should:

  • be able to classify different types of multiagent systems
  • be able to apply and understand the meaning of the agent concept in a distributed environment
  • be able to design and use appropriate framework for agent communication and information sharing processes
  • have gained detailed knowledge of the different research methods, especially game theory and swarm intelligence, which are used for modelling the dynamics of distributed agent systems
  • have gained practical experience in modeling multiagent systems though computer simulation and experimentation

Admission

PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.

If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.

PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.

Prerequisites

Recommended previous knowledge

Programming experience equivalent to INF2220 - Algorithms and Data Structures. The course INF3490 - Biologically inspired computing may also give a useful background.

Overlapping courses

10 credits overlap with UNIK4950 - Multi-agent systems

Teaching

2 hours lecture plus 1 hour group work each week.

2 mandatory assignments and 1 written report must be approved in order for you to take the exam.

Examination

Oral exam at the end of the semester (in case of many students, there may be a written exam instead). All of the mandatory assignments must be approved in order for you to attend the exam. 

Language of examination

You may write your examination paper in Norwegian, Swedish, Danish or English.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Explanations and appeals

Resit an examination

Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.

Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Facts about this course

Credits

10

Level

PhD

Teaching

Every autumn

Examination

Every autumn

Teaching language

Norwegian (English on request)