Course Swarm Intelligence WS 2014/2015

Exam in SS15

+++++++ Exam will be on Monday 20.07.2015 at 9 - 11 in room G29-307 +++++++

Exam of WS14/15

Here you can find the exam questions of this year. The grading scales can be found here.

Results of the exam are already online. Here is the statistic to the exam:

Notenverteilung-SI

Post-Exam Review:

Students can review their exams on Thursday 9th of April at 10:45 in room G29-018.

Description

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 behaviorthrough the local interactions between its members. This collective property can be very well 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
(Self-assembly swarm)

Lectures

The lectures take place: Mondays 15-17 in G29 – 307

Slides

Videos related to the slides

Slide SI-2-14: Almost constant attraction and unbounded repulsion
Slide SI-2-17: Attraction and repulsion function-III
Slide SI-2-28: Swarm Cohesion
Slide SI-2-31: Case 1 – Repulsion
Slide SI-2-31: Case 2 – Attraction
Slide SI-2-36: Pattern Formation and Tracking
Slide SI-2-67: Robust against failures
Slide SI-2-68: OSCAR From University of Lübeck
Slide SI-3-35: Gap Search1, Gap Search2
Slide SI-3-40: PSO (Quick Convergence, Local Optimum)
Slide SI-4-3: Ant Sorting

Recorded lectures

Chapter 0 - Chapter 1: Monday 13.10.2014 (Normale Size - Reduced Size)
Chapter 2 (Slides 1 - 36): Monday 20.10.2014 (Normale Size - Reduced Size)
Chapter 2 (Slides 36 - 65): Monday 27.10.2014 (Normale Size - Reduced Size)
Chapter 2 (Slides 65 - 70), Chapter 3 (Slides 1 - 29): Monday 03.11.2014 (Normal Size - Reduced Size 1 - Reduced Size 2)
Chapter 3 (Slides 30 - 56): Monday 10.11.2014 (Normal Size)
Chapter 3 (Slides 57 - 75): Monday 17.11.2014 (Normal Size)
Chapter 3 (Slides 75 - 98): Monday 24.11.2014 (Normal Size)
Chapter 3 (Slides 98 - 103), Chapter 4 (Slides 1 - 29): Monday 01.12.2014 (Normal Size)
Chapter 4: Monday 15.12.2014 (Normal Size)
Chapter 4 and 5: Monday 19.01.2015 (Normal Size)
Chapter 6: Monday 26.01.2015 (Normale Size)

Exercises

Tutorials take place: Fridays 11-13 in G29-307

Assignments

Solutions to the assignments

Tutorial 1 (Chapter 2 - part 1) - 24.10.2014
Tutorial 2 (Chapter 2 - part 2) - 07.11.2014
Tutorial 3 (Chapter 3 - part 1) - 14.11.2014
Tutorial 4 (Chapter 3 - part 2) - 21.11.2014
Tutorial 5 (Chapter 3 - part 3) - 28.11.2014
Tutorial 6 (Chapter 4) - 09.01.2015 - 23.01.2015

Videos realted to the assignments

Chapter 2 (Assignment 1- (c), (d), (f), (g), Assignment 4, Assignment 5, Assignment 7, Assignment 8 - (a), (c), (d))
Chapter 4

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