Project EVOSOS successfully concluded!

Within the project EVOSOS, we investigated how evolutionary computation can be applied to find the appropriate local rules that provide the desired emergent global behavior for a given system. In particular, we propose a design methodology built on meta-heuristic search that can guides the designer throughout the whole engineering process. Additionally, we investigate the evolvability of self-organizing technical systems via several case studies focusing on the effects of certain design decisions explained in the proposed methodology. First, a self-organizing cellular automata model is described that is evolved to present a desired 2D structure. Using this example the connection between problem complexity and evolvability is discussed.
Two further studies focus on evolutionary swarm robotics. In the first one, we discuss the effects of various interaction interfaces and their effects on the quality of the evolved solutions. We find that seemingly identical interfaces can produce significantly different group behavior. The second experiment investigates how a self-organizing team of soccer robots can be evolved. Here, we study the effects of different agent controller structures and interface interpretation models.
A further outcome of the project is the evolutionary software framework FREVO, which implements the proposed design methodology and thus aids engineers and researchers working with self-organizing systems.

Publications (with link to fulltexts):

• I. Fehervari and W. Elmenreich. Evolution as a tool to design self-organizing systems. In Self-Organizing Systems, volume LNCS 8221, pages 139–144. Springer Verlag, 2014.
• István Fehérvári, On Evolving Self-organizing Technical Systems, PhD Dissertation, Alpen-Adria-Universität Klagenfurt, 2013.
• I. Fehérvári, V. Trianni, and W. Elmenreich. On the effects of the robot configuration on evolving coordinated motion behaviors. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE, June 2013.
• I. Fehérvári, A. Sobe, and W. Elmenreich. Biologically sound neural networks for embedded systems using OpenCL. In Proceedings of the International Conference on NETworked sYStems (NETYS 2013). Springer Verlag, May 2013.
• R. M. W. Masood, J.Klinglmayr, I. Fehervari, W. Watzl, C. Bettstetter: Demo Abstract: Synchronization using Inhibitory and Excitatory Coupling: From Theory to Practice, in: The 32nd IEEE International Conference on Computer Communications, IEEE, Piscataway (NJ), April 2013.
• 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, pages 201–204, Vienna, Austria, April 2012.
• A. Sobe, I. Fehérvári, and W. Elmenreich. FREVO: A tool for evolving and evaluating self-organizing systems. In Proceedings of the 1st International Workshop on Evaluation for Self-Adaptive and Self-Organizing Systems, Lyon, France, September 2012.
• W. Elmenreich and I. Fehérvári. Evolving self-organizing cellular automata based on neural network genotypes. In Proceedings of the Fifth International Workshop on Self-Organizing Systems, volume LNCS 6557, pages 16–25. Springer Verlag, 2011.
• I. Fehervari, B. Lenart: Using an Adaptive Neuro-Fuzzy Inference System for Adaptive Inventory Control, in: Proceedings of the International Conference on Innovative Technologies (IN-TECH) 2011, Czech Technical University, Faculty of mechanical engineering, Department of manufacturing technology, Prague, 2011, S. 43 - 48.
• O. Maurhart, W. Elmenreich, I. Fehervari, A. Bouchachia: Evaluation of Robustness and Performance of Environmental Influences on Evolutionary Algorithms compared to Ant Colony Systems, in: European Conference on Complex Systems (ECCS'11 Vienna), Löcker Verlag, Wien, 2011, S. 98 - 99.