IE501714 - Swarm intelligence


Course content

1. agent system modelling

• systems theory and agent-based modelling.

• individual agents.

• passive particle agents.

• producer-consumer agents.

• active particle agents.

• intelligent agents.

2. social agents

• flocking behaviour.

• flocking behaviour applications • agents queuing and homing.

• boids.

3. Particle swarm optimisation (PSO)

• PSO algorithm.

• path planning applications.

• PSO for path planning.

• Dynamic replanning with obstacles.

4. Ant colony optimisation (ACO)

• ACO algorithm.

• Bees Colony algorithm.

5. Evolutionary Agents (EA)

• learning agents.

• Genetic algorithms.

• multi-objective optimisation using GA (MOOGA).

6. Selected topics

• multi-robot path planning.

• multi-robot task allocation.

Learning outcome


• Have knowledge of intelligent agents for modeling of industrial, social and biological systems.

• Have knowledge of modeling of generic intelligent agents in complex landscapes.

• Have knowledge of modeling of social agents in complex landscapes.

• Have knowledge of the learning of intelligent agents in complex landscapes.


• Have skills in using intelligent agents to solve optimization problems in complex landscapes.

• Have skills in developing simulation models based on swarms of intelligent agents.

General competence:

• Have general knowledge about the subject's possibilities and limitations.

• Have general knowledge of being able to analyze, disseminate and communicate the topic issues.

• Have general knowledge about how intelligent agents can contribute to innovation processes.

Learning methods and activities

Lectures, discussion at group and class level, three mandatory assignments covering the whole course. The mandatory assignments are performed in groups of 2-3 students.

Three mandatory assignments are to be handed in and approved in order to get access to the exam.

Compulsory assignments

  • Mandatory assignment

Further on evaluation

Oral exam

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Admission to a programme of study is required:
Master in engineering in Simulation and Visualization (880MVS)

Course materials

The course material will be announced at the start of the course.

More on the course



Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  SPRING 2020

Language of instruction: English

Location: Ålesund

Subject area(s)
  • Engineering Subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of ICT and Natural Sciences



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