The Mid-Term Exam will take place on Tuesday, December 05 from 13:15 to 14:00 in Room G29-307. Please register in the e-learning course, so we know how many students will attend the exam.
This course provides in-depth knowledge about swarm intelligence in technical systems. In swarm intelligence, we deal with a group of simple and usually homogenous individuals with simple rules. Usually, swarms can achieve a complex and intelligent behaviour using local interactions between its members. This collective property can be used in technical systems. One advanced application of swarm intelligence is in 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, analysed 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 multiagent systems
- Division of labour and task allocation
- Swarm clustering and sorting
- Ant systems and optimization
Part 3: Applications
- Swarm localization and display
- Swarm robotics
There is no registration before the lecture starts. If you are interested in participating in the Swarm Intelligence lecture and exercises, you will receive all the necessary information in the first lecture.
This lecture will take place in presence format every Tuesday 14:30 to 16:00 in room G29-307. We will record the lectures and upload them online on Mediasite.
The first lecture will be held on October 10.
No lectures on 24.10.2023 and 14.11.2023
- Chapter 1: Organization and Introduction
- Chapter 2 (part 1): Swarm Aggregation
- Chapter 2 (part 2): Swarms in Known Environments, Emergence and Entropy
- Chapter 3 (part 1): Swarms in unknown environments: Optimization algorithms
- Chapter 3 (part 2): Multi-Objective Particle Swarm Optimization
- Chapter 4 (part 1): Ant Systems: Sorting and Division of Labour
- Chapter 4 (part 2): Ant systems: Ant Colony Optimization
- Chapter 5: Swarm Localization
- Chapter 6: Collective Decision-making
- Chapter 7: Swarm Robotics
Please refer to this link /OVGU/Fakultäten/Informatik (FIN)/Institut für Intelligente Kooperierende Systeme (IKS)/AG Computational Intelligence/Swarm Intelligence for the recorded lectures. Note: Here you must log in with your URZ account, otherwise the list of videos is empty. To log in, you have to click the button labelled "GU" and supply your URZ credentials. You may need to follow the link a second time after you completed the login procedure.
We will upload the recorded lectures after each lecture.
Tutorials take place on Tuesday 13:15 to 14:45 in Room G29-307 (right before the lecture). You have to attend the tutorials. The first tutorial will be held on October 17.
To meet the large demand for the swarm intelligence course, we offer a live tutorial in the lecture hall with explanations for solving the tutorials.
Solve the assignments yourself (This is how you can maximize your learning experience!).
- After solving each assignment, refer to the tutorials to check your results
- Ask questions that you have during the tutorials or via moodle.
To be able to write the exam, you must fulfil the following criterion:
- You have to pass a midterm exam. We will provide the details during the lectures.
The assignments will be published here during the semester.
|10. 10.||No tutorial|
|17. 10.||Sheet 1||Solution|
|24. 10.||Sheet 2 SI-Programming1.ipynb||Solution|
|31. 10.||No tutorial (federal holiday)|
|07. 11.||Sheet 3 SI-Programming2.ipynb||Solution|
|14. 11.||Sheet 4 SI-Programming3.ipynb||Solution|
|05. 12.||Midterm Exam|
|12. 12.||Sheet7 SI-Programming6.ipynb|
|23. 01.||Questions and Answers|
Exams from past years
- Exam of WS 21/22
- Exam of WS 17/18 - annotated version
- Exam of WS16/17 - annotated version
- Exam of WS15/16 - annotated version
- Exam of WS14/15 - annotated version
- Exam of WS13/14
- 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