INFO-H-414 : Swarm Intelligence

Lecturers

Objective

To let students have a basic understanding of swarm intelligence principles

Contents

Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In particular, the discipline focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. Examples of systems studied by swarm intelligence are colonies of ants and termites, schools of fish, flocks of birds, herds of land animals. Some human artifacts also fall into the domain of swarm intelligence, notably some multi-robot systems, and also certain computer programs that are written to tackle optimization and data analysis problems. The course will present a number of swarm intelligence systems and will give the opportunity to experiment with them.

Overheads

Practical lessons material

Schedule

S22 - Lesson 01 - Thu 13.02.2020 - 2:00pm-4:00pm - S.H2213

S23 - Lesson 02 - Thu 20.02.2020 - 2:00pm-4:00pm - S.H2213

S23 - Lesson 03 - Thu 20.02.2020 - 4:00pm-6:00pm - Descartes (UB4.329a) and Platon (J.1.104)

S24 - Lesson 04 - Thu 27.02.2020 - 2:00pm-4:00pm - S.H2213

s24 - Lesson 05 - Thu 27.02.2020 - 4:00pm-6:00pm - Aristote (UB4.126)

S26 - Lesson 06 - Thu 12.03.2020 - 2:00pm-4:00pm - Aristote (UB4.126)

S26 - Lesson 07 - Thu 12.03.2020 - 4:00pm-6:00pm - Aristote (UB4.126)

S27 - Lesson 08 - Thu 19.03.2020 - 2:00pm-4:00pm - online via email to assistants

S27 - Lesson 09 - Thu 19.03.2020 - 4:00pm-6:00pm - online via email to assistants

Due to the COVID-19 lockdown, the theoretical and practical sessions for the remaining part of the Swarm Intelligence course (which concerns swarm robotics) will be given through Office 365 Teams. Students can connect here: Connect to Office 365 Teams

If you have any questions concerning this part of the course you can contact Prof. Birattari via email: mbiro@ulb.ac.be

S28 - Lesson 10 - Thu 26.03.2020 - 2:00pm-4:00pm -

S28 - Lesson 11 - Thu 26.03.2020 - 4:00pm-6:00pm -

S29 - Lesson 12 - Thu 02.04.2020 - 2:00pm-4:00pm -

S29 - Lesson 13 - Thu 02.04.2020 - 4:00pm-6:00pm -

S32 - Lesson 14 - Thu 23.04.2020 - 2:00pm-4:00pm -

S32 - Lesson 15 - Thu 23.04.2020 - 4:00pm-6:00pm -

S33 - Lesson 16 - Thu 30.04.2020 - 2:00pm-4:00pm -

S33 - Lesson 17 - Thu 30.04.2020 - 4:00pm-6:00pm -

S34 - Lesson 18 - Thu 07.05.2020 - 2:00pm-4:00pm -

Exam modalities

The first session exams will take place on June 22nd/23rd/24th, 2020

However, to increase flexibility, it will also be possible for the students to choose to have their exam on the 16th or the 18th. In this case they should let us know, at the time they deliver their project (June 6, 2020), whether they wish to have their examination on the 16th, the 18th or the 22nd/23rd/24th. We will try as much as possible to meet the students requests. If no indication is provided, it will be assumed that the student wishes to take his/her exam on the 22nd/23rd/24th.

Students should also provide, together with the delivery of their project, a telephone number or Skype address where we could call them in case there is any problem with the TEAMS connection. Please place your telephone number on the project front page, just beside your name.

Project first session

The project is composed of two parts, covering the two subjects studied in class: swarm robotics and optimization. In the first part, the students are required to solve, by hand, a collective decision problem in which a swarm must select the best option among set of possible alternatives. In the second part, the students must identify parameters of their solution to the collective decision problem, and fine-tune these parameters using a particle swarm optimization algorithm.

The project description is available at the following link: Final Project SI - First Session 2020

Project rules

The project counts for 50% of the final grade. The two parts of the project (swarm robotics and optimization) are equally important and comprise one single project. Therefore, in order to deliver a complete project, the students have to tackle the two parts.

The project submission deadline is June 6 at 23:59. Delay on the submission will entail a penalty of 1 point every 12 hours of delay on the final evaluation of the project. Maximum delays is June 9 at 23:59. After this deadline, the exam is failed.

The students have to submit, via the Assignments of TEAMS, the following elements: Their code in digital format together with information on how to test it; A short report of maximum 7 pages written in English that describes their work.

Second session

There will be a second session. The exam modalities will be the same as in the first session. The description of a new project will be made available in early July.

Bibliography

  • Dorigo M. & T. Stützle (2004). Ant Colony Optimization. Cambridge, MA: MIT Press/Bradford Books
  • Bonabeau E., M. Dorigo & G. Theraulaz (1999). Swarm Intelligence: From Natural to Artificial Systems. New York, NY: Oxford University Press
  • Francesca G. & M. Birattari (2016). Automatic Design of Robot Swarms: Achievements and Challenges. Frontiers in Robotics and AI. https://www.frontiersin.org/article/10.3389/frobt.2016.00029
  • Birattari M., A. Ligot, D. Bozhinoski et al (2019). Automatic Off-Line Design of Robot Swarms: A Manifesto. Frontiers in Robotics and AI. https://www.frontiersin.org/article/10.3389/frobt.2019.00059

Teaching methods

Ex cathedra and projects. Course taught in English.

 
teaching/infoh414.txt · Last modified: 2020/06/02 16:16 by mdorigo