Swarm Intelligence

 +++ The review for the exam will be in the first week of the new semester: April 8 at 13:00 to 15:00 +++

Description

This course provides a deep knowledge about swarm intelligence in technical systems. In swarm intelligence, we deal with a group of simple and usually homogenous individuals with simple rules. The swarm can achieve a complex and intelligent behavior using local interactions between its members. This collective property can be used in technical systems as well as in optimization of complex problems. One advanced application of swarm intelligence is in the area of swarm robotics in which simple small robots can collectively learn to achieve some predefined complex tasks. During this course, the algorithms of swarm intelligence are presented, analyzed and compared. The following topics will be covered:

Part 1: Fundamentals of swarm intelligence

  • Swarm stability and stability analysis
  • Swarm aggregation
  • Swarm in known environments
  • Swarm in unknown environments: Particle Swarm Optimization
  • Dynamic Optimization
  • Multi-Objective Particle Swarm Optimization 

Part 2: Swarm and multi-agent systems

  • Division of labor and task allocation
  • Swarm clustering and sorting
  • Ant systems and optimization

Part 3: Applications

  • Swarm localization and display
  • Swarm robotics

Lecturer

Lectures 

The lectures take place: Wednesday 11:00 -12:30 in G29 307. The first Lecture will take palce on Wednesday 16 October 2019 (Please note, we start at 11:00)

 

Slides

 

Recorded lectures

Please refer to http://mediasite.ovgu.de/Mediasite/Catalog/catalogs/iks-si for the recorded lectures. Note: Here you require your URZ account. 

 

Tutorials:

In order to meet the large demand for the swarm intelligence course, we offer every week one tutorial for all in the lecture hall 307 (Thursdays 15:15 - 16:45).

In order to be able to write the exam you must fulfill the following criteria: 

  1. Attend all the tutorials (there will be a list)
  2. The assignments need to be solved at home, before the tutorial
  3. *** New *** You have to pass a midterm exam. We will provide the details during the lectures: you can register for the mid-term exam here: https://iws.iws.cs.ovgu.de:8443/frs/subscribe/MidTermExamSI

 

Assignments

The assignments will be published a week before the tutorial.

 

24.10

Sheet 1

7.11

Sheet 2 - The code for Task 4: Swarm-Follow.ipynb

14.11

Sheet 3 -> Solution

22.11

Midterm Exam, 13:00 to 15:00 in HS

28.11

 Sheet 4

5.12

No Tutorial, Sheet 5 will be changed for next week.

12.12

 Sheet 5 - one task (Hypervolume) was added to the version from last week!

19.12

 Sheet 6

9.1

Sheet 7

16.1

 Sheet 8

23.1

Wrap Up (Please send your Questions) + Sheet 9

30.1

Q & A before Exam (Please send your Questions) + Solutions

Exams from past years

 

 

 Literature

  • Veysel Gazi and Kevin M. Passino, Swarm Stability and Optimization, Springer, 2011
  • Eric Bonabeau, Marco Dorigo and Guy Theraulaz, Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press, 1999
  • Andries Engelbrecht, Fundamentals of Computational Swarm Intelligence, Wiley 2006
  • James Kennedy and Russel Eberhart, Swarm Intelligence, Morgan Kaufmann, 2001
  • Zbigniew Michalewicz and David Fogel, How to solve it: Modern Heuristics, Springer, 2001
  • Marco Dorigo and Thomas Stützle, Ant Colony Optimization, The MIT Press, 2004
  • C. Solnon: Ant Colony Optimization and Constraint Programming. Wiley 2010
  • Gerhard Weiss, Multiagent Systems: A modern approach to distributed artificial systems, The MIT Press, 2000
  • Christian Müller-Schloer, Hartmut Schmeck and Theo Ungerer, Organic Computing A Paradigm Shift for Complex Systems, Springer, 2011

Last Modification: 25.02.2020 - Contact Person: Webmaster