Authors:
Lukas König
;
Sanaz Mostaghim
and
Hartmut Schmeck
Affiliation:
Karlsruhe Institute of Technology, Germany
Keyword(s):
Evolutionary robotics, Swarm robotics, Success prediction, Mathematical model, Markov chain, Selection.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
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:
In this paper, a theoretical and experimental study of the influence of environments on the selection process in evolutionary swarm robotics is conducted. The theoretical selection model is based on Markov chains. It is proposed to predict the success rate of evolutionary runs which are based on a selection mechanism depending on implicit environmental properties as well as an explicit fitness function. In the experiments, the interaction of explicit and implicit selection is studied and a comparison with the model prediction is performed. The results indicate that the model prediction is accurate for the studied cases.