INFO-H-414 : Swarm Intelligence

• Marco Dorigo
• Mauro Birattari

To let students have a basic understanding of swarm intelligence principles

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.

Introduction to Swarm Intelligence

Clustering

Particle Swarm Optimization (PSO)

Ant Colony Optimization (ACO)

Introduction to Swarm Robotics

Division of labour and task allocation

Automode

Swarm robotics material

Ant Colony Optimization and Particle Swarm Optimization:

* The TSP solved using Ant System

* Class exercise 1

* Exercise 1

* ACO template for the TSP

* Instances

* Scripts

* Template of ACO for the TSP (implemented)

* Scripts (updated)

* Exercise 1 (solved)

* Advanced ACO algorithms

* Class exercise 2

* Exercise 2

* ACOTSP (implementation of various ACO algorithms applied to the TSP)

* Exercise 2 (solved)

* Particle Swarm Optimization

* Class exercise 3

* Exercise 3

* PSO template

* Template of PSO implemented

* Class exercise 3 (solved)

* Exercise 3 (solved)

Swarm Robotics:

Instructions for the practical sessions are available through Office 365 Teams:

* Connect to Office 365 Teams

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 -

Exams will take place online, using the ULB TEAMS application

The second session exam will take place between August 12th and August 19th, 2020

The exact schedule will be communicated once we know the exact number of students

The project, as it was the case for the first session, will be composed of two parts, covering the two subjects studied in class: swarm robotics and optimization.

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 both parts.

The project submission deadline is August 9 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 August 11 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.

• 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

Ex cathedra and projects. Course taught in English.