CHAIR OF

COMPUTATIONAL

INTELLIGENCE

Announcements

• The lectures and video recorded tutorials can be streamed via mediasite
• There will be question and answer sessions held via ZOOM and we will create a forum in the e-learning plattform
• Registration for the exercises via LSF.
• This webpage will be updated during the course, please regularly check for updates

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

• Sanaz Mostaghim (Course)
• Sebastian Mai (Tutorials)

Lectures 

Lectures will be streamed on the ovgu-mediasite. (See "Recorded Lectures" below). During corona there will be no live-lectures.

Slides

• Organisation
• Chapter 1: Introduction
• Chapter 2:
  • Swarm aggregation 
  • Swarm aggregation in known environments, Measuring self-organization and Robust formations
• Chapter 3:
  • Swarms in unknown and dynamic environments
  • Swarms and Multi-Objective Optimization 
• Chapter 4:
  • Ant Systems: Sorting and Division of Labor
  • Ant Colony Optimization
• Chapter 5: Localization Methods in Swarms
• Chapter 6: Swarm Robotics

Recorded Lectures

In order to plan the lectures in a structured way, we provide you the following lecture plan. You should learn the material for each week by referring to the online videos and slides:

Tutorials:

In order to meet the large demand for the swarm intelligence course, we offer tutorial questions and video recorded solutions and explainations for solving the tutorials.

To register for the course in the elearning platform, please go to elearning.ovgu.de and register to the course "Swarm Intelligence Tutorials". The enrolment key is the same as the password for the slides (please refer to the organization video).

Solve the assignments yourself (This is how you can maximise your own learning experience!)

1. After solving each assigment refer to the video-recorded explanation to check your results
2. Ask questions that you have in the Q&A sessions or the forum

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

•  You have to pass a midterm exam. We will provide the details during the lectures

Assignments

The assignments will be published during the semster.

Similar to the lectures we will publish assignments and video-solutions in a structured way during the semester.

 For the programming excercises you can use google-colab if you do not want to install jupyter on your own pc.

Exams from past years

• Exam of WS 17/18 - annotated version
• Exam of WS16/17 - annotated version
• Exam of WS15/16 - annotated version
• Exam of WS14/15 - annotaed version
• Exam of WS13/14

 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