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

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

S28 - Lesson 10 - Thu 26.03.2020 - 2:00pm-4:00pm - Ask Prof. Birattari - mbiro@ulb.ac.be

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 -

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

Will be added later

Will be added later

Will be added later

• 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.