FREVO presented at SASO'12, Lyon

Anita Sobe and Istvan Fehervari are currently at the SASO 2012 in Lyon, the main conference on self-organizing and self-adaptive systems, with approximately 100 attendees. The topics of the talks are very wide spread and therefore the attendees and speakers come from different fields where they apply and analyze various SASO systems.

The first day we attendted the Workshop EVAL4SASO, a special session dedicated for the problem of evaluating such complex SASO systems. Here, we presented our paper:

A. Sobe, I. Fehervari, W. Elmenreich

FREVO: A Tool for Evolving and Evaluating Self-organizing Systems

In IEEE SASO Workshop Eval4SASO, Lyon, France, September 2012

It presents a generic evolutionary framework for rapid prototyping and evaluating research ideas on the design and behavior of evolved complex systems. To illustrate its capabilities, we demonstrated a short demo on a sample problem of dynamic pricing in smart microgrids. FREVO is easy to use and we hope it will assist many researchers and engineers. For further details and downloads, see:

http://frevo.sourceforge.net/

The initial feedback we obtained on the conference was very promising, opening many new possibilities for further joint work in this field. 

To see what is possible with this tool, please check this interesting video on evolving a team of robots playing soccer:

Evolving a team of self-organizing UAVs to address spatial coverage problems

An example for engineering a distributed algorithm using evolutionary methods was presented at the European Meeting on Cybernetics and Systems Research (EMCSR 2012). The task was to evolve a distributed control algorithm for flying UAV drones to cover an area. The problem of having multiple mobile agents covering (or as we say in robotics, "sweeping") an area is relevant for many applications like lawn mowing, snow removal, floor cleaning, environmental monitoring, communication assistance and several military and security applications. The work by Istvan Fehervari, Wilfried Elmenreich and Evsen Yanmaz describes a simple grid-based abstraction of the problem which was used to test two evolved and one handcrafted control algorithm in comparison to reference algorithms like random walk and random direction.

 Slides (via slideshare):

I. Fehérvári, W. Elmenreich, and E. Yanmaz. Evolving a team of self-organizing UAVs to address spatial coverage problems. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts (ISSN: 2227-7803), Vienna, Austria, April 2012.