« Previous Abstract"Sexual Behavior of the Sugarcane Hairy Borer, Hyponeuma taltula (Lepidoptera: Erebidae): Evidence for a Female-Released Sex Pheromone"    Next Abstractorco Mutagenesis Causes Loss of Antennal Lobe Glomeruli and Impaired Social Behavior in Ants »

Biol Cybern

Title:		Self-organisation and communication in groups of simulated and physical robots
Author(s):		Trianni V; Dorigo M;
Address:		"Universite Libre de Bruxelles, IRIDIA CP 194/6, Av. Franklin Roosevelt 50, Brussels, 1050, Belgium. vtrianni@iridia.ulb.ac.be"
Journal Title:		Biol Cybern
Year:		2006
Volume:		20060705
Issue:		3
Page Number:		213 - 231
DOI:		10.1007/s00422-006-0080-x
ISSN/ISBN:		0340-1200 (Print) 0340-1200 (Linking)
Abstract:		"In social insects, both self-organisation and communication play a crucial role for the accomplishment of many tasks at a collective level. Communication is performed with different modalities, which can be roughly classified into three classes: indirect (stigmergic) communication, direct interactions and direct communication. The use of stigmergic communication is predominant in social insects (e.g. the pheromone trails in ants), where, however, direct interactions (e.g. antennation in ants) and direct communication (e.g. the waggle dance in honey bees) can also be observed. Taking inspiration from insect societies, we present an experimental study of self-organising behaviours for a group of robots, which exploit communication to coordinate their activities. In particular, the robots are placed in an arena presenting holes and open borders, which they should avoid while moving coordinately. Artificial evolution is responsible for the synthesis in a simulated environment of the robot's neural controllers, which are subsequently tested on physical robots. We study different communication strategies among the robots: no direct communication, handcrafted signalling and a completely evolved approach. We show that the latter is the most efficient, suggesting that artificial evolution can produce behaviours that are more adaptive than those obtained with conventional design methodologies. Moreover, we show that the evolved controllers produce a self-organising system that is robust enough to be tested on physical robots, notwithstanding the huge gap between simulation and reality"
Keywords:		"Algorithms Analysis of Variance *Animal Communication Animals *Artificial Intelligence Behavior, Animal/physiology Biological Evolution Computer Simulation Insecta *Models, Biological Neurons/physiology *Robotics/instrumentation Social Behavior;"
Notes:		"MedlineTrianni, Vito Dorigo, Marco eng Germany 2006/07/06 Biol Cybern. 2006 Sep; 95(3):213-31. doi: 10.1007/s00422-006-0080-x. Epub 2006 Jul 5"