Authors:
Giuseppe Morlino
;
Vito Trianni
and
Elio Tuci
Affiliation:
National Research Council, Italy
Keyword(s):
Swarm robotics, Collective behaviour, Perceptual discrimination, Evolutionary algorithms, Artificial neural networks.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Life
;
Computational Intelligence
;
Evolutionary Computing
;
Evolutionary Robotics and Intelligent Agents
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
;
Swarm/Collective Intelligence
Abstract:
We present a study that aims at understanding how perception can be the result of a collective, self-organising process. A group of robots is placed in an environment characterized by black spots painted on the ground. The density of the spots can vary from trial to trial, and robots have to collectively encode such density into a coherent flashing activity. Overall, robots should prove capable of perceiving the global density by exploiting only local information and robot-robot interactions. We show how we can synthesize individual controllers that allow collective perception by exploiting evolutionary robotics techniques. This work is a first attempt to
study cognitive abilities such as perception, decision-making, or attention in a synthetic setup as result of a collective, self-organising process.