CS&E Seminar: Vito Trianni - 27 May 2010 - 12.00 @ Aula Magna

Speaker: Vito Trianni - Institute of Cognitive Sciences and Technologies, National Research Council, Rome (ISTC-CNR)

Title: Evolution, Self-Organisation and Swarm Robotics

Date: 27 May 2010, 12:00 noon

Location: Aula Magna at DIS

Abstract. The activities of social insects are often based on a self-organising process, that is, a process in which a spatio-temporal pattern at the global level of a system emerges solely from the numerous interactions among the lower-level components of the system. In a self-organising system such as an ant colony, there is neither a leader that drives the activities of the group, nor the individual ants are informed of a global recipe or blueprint to be executed. On the contrary, each single ant acts autonomously following simple rules and locally interacting with the other ants. As a consequence of the numerous interactions among individuals, a coherent behaviour can be observed at the colony level. A similar organisational structure is definitely beneficial for a swarm of autonomous robots. Moreover, the features that characterise a self-organising system (i.e., decentralisation, flexibility and robustness) are highly desirable also for a swarm of autonomous robots. The main problem that has to be faced in the design of a self-organising robotic system is the definition of the individual rules that lead to the desired collective behaviour. A possible solution to this design problem relies on artificial evolution as the main tool for the synthesis of self-organising behaviours. I will present a case study in which evolutionary techniques are applied to the design of self-organising synchronisation in a group of autonomous robots. Artificial evolution proves to be capable of synthesising minimal synchronisation strategies based on the dynamical coupling between robots and environment. The obtained results are analysed under a dynamical systems perspective, which allows us to uncover the evolved mechanisms and to predict the scalability properties of the self-organising synchronisation with respect to varying group size. The knowledge acquired by the dynamical analysis allows to pinpoint the critical aspects that constrain the system, which can be later modified in order to re-engineer the evolutionary process towards better solutions.

References:
- V. Trianni and S. Nolfi. Self-Organising Sync in a Robotic Swarm. A Dynamical System View. IEEE Transactions on Evolutionary Computation, 13(4):722-741, 2009.
- V. Trianni, S. Nolfi, and M. Dorigo. Evolution, self-organisation and swarm robotics. In C. Blum and D. Merkle, editors, Swarm Intelligence. Introduction and Applications, pages 163-192, Natural Computing Series, Springer Verlag, Berlin, Germany, 2008.
- V. Trianni and S. Nolfi. Re-Engineering Evolution: A Study In Self-Organising Synchronisation. Proceedings of the 12th International Conference on Artificial Life (ALIFE XI). 19-23 August 2010, Odense, Denmark.

Vito Trianni received a master degree in computer science engineering at the Politecnico di Milano (IT), and a DEA and PhD from the Université Libre de Bruxelles, working at the IRIDIA lab on swarm and evolutionary robotics. Currently, he is a researcher at the ISTC-CNR in Rome, Italy. His research interests span over evolutionary robotics, swarm intelligence and swarm robotics, self-organising systems, and the application of dynamical systems theory to the study of cognitive processes. He has published more than 30 papers in international scientific journals and peer-reviewed conference proceedings, and the book "Evolutionary Swarm Robotics" within the Springer's Series in Computational Intelligence. Per qualsiasi ulteriore informazione, non esitate a contattarmi.

Web page of the Seminars series: http://www.dis.uniroma1.it/~seminf/