Authors:
Emmanuel Sapin
1
;
Jean Louchet
2
and
Evelyne Lutton
3
Affiliations:
1
INRIA-Saclay, France
;
2
INRIA-Saclay;Artenia, France
;
3
INRIA Saclay, France
Keyword(s):
Evolutionary algorithm, Cooperative coevolution, Computer vision, Fly algorithm, Image sensor.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Co-Evolution and Collective Behavior
;
Computational Intelligence
;
Evolution Strategies
;
Evolutionary Computing
;
Evolutionary Robotics and Intelligent Agents
;
Soft Computing
Abstract:
Cooperative coevolution algorithms (CCEAs) usually represent a searched solution as an aggregation of several individuals (or even as a whole population). In other terms, each individual only bears a part of the searched solution. This scheme allows to use the artificial Darwinism principles in a more economic way, and the gain in terms of robustness and efficiency is important. In the computer vision domain, this scheme has been applied to stereovision, to produce an algorithm (the fly algorithm) with asynchronism property. However, this property has not yet been fully exploited, in particular at the sensor level, where CMOS technology opens perpectives to faster reactions. We describe in this paper a new coevolution engine that allow the Fly Algorithm to better exploit the properties of CMOS image sensors.