Admission requirements
Bachelor course Natural Computing is a helpful prerequisite, but not mandatory.
No specific other requirements.
Description
Swarm based computing is a modern artificial intelligence discipline that is concerned with the design of multi-agent systems with applications. It is embedded in the biological study of self-organized behaviors in social animals, e.g., the collective behavior of social insects such as ants and bees, as well as flocks of birds and schools of fish. Instead of a sophisticated controller that governs the global behavior of the system, the swarm intelligence principle is based on many unsophisticated entities that cooperate in order to exhibit a desired behavior (self-organization). For example, without any master blueprint bees are able to build complex hive in cooperation.
Scientists have applied these principles to new approaches, for instance, optimization and swarm robotics. Through this research seminar, we will provide an overview of swarm intelligence as well as a collection of some of the most interesting up-to-date applications from different domains. Furthermore, students will learn studying, processing and presenting scientific material about swarm intelligence through this seminar.
Techniques from swarm based computing considered in the seminar include the following:
Ant Colony Optimization
Artificial Bee Colonies
Particle Swarm Optimization
Swarm Robotics
Firefly algorithms
Division of Labor Models
Principles of Self-Organization in Social Insects
Agent Based Modeling and its Relation to Swarm Based Computing
Differential Evolution, Gravitational Search and Related Metaheuristics
Application areas include specific bioinformatics applications, such that bioinformatics students can specialize on an application in their field of interest. Selected applications include, e.g., sequence alignment and protein folding.
Course objectives
Having successfully finished this seminar, the students are able to:
study and understand scientific literature reflecting state-of-the-art work in swarm computing approaches and related fields
work in groups and conduct group discussions including critical reflections about the subject matter
write a scientific essay summarizing the literature read about a particular topic swarm based computing
prepare and give a presentation about a particular topic in swarm based computing
understand and execute specific swarm based computing algorithm and, if possible, apply it to a small test problem in the relevant application area chosen.
Timetable
The most recent timetable can be found at the LIACS website
Mode of instruction
Writing a scientific essay/project report
Oral presentation
Group discussion
Collaboration with other students
Practical work with software (implementations of swarm based algorithms)
Assessment method
The final mark is composed of
The project report (50%)
The presentation slides and oral presentation (20%)
The software demonstration (20%)
Participation in group discussions (10%)
Reading list
Ant Colony Optimization, Marco Dorigo and Thomas Stützle, the MIT press, 2004
Swarm Intelligence – From Natural to Artificial Systems, Eric Bonabeau, Marco Dorigo and Guy Theraulaz, Oxford University press, 1999
Swarm Intelligence, James Kennedy, Russell C. Eberhart, and Yuhui Shi, Academic press, 2001
Registration
You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.
There is a limited capacity for students from outside the master Computer Science programme. Please contact the study-advisor.
Contact information
Study coordinator Computer Science, Riet Derogee