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|Title=A Markov-Chain-Based Model for Success Prediction of Evolution in Complex Environments
 
|Title=A Markov-Chain-Based Model for Success Prediction of Evolution in Complex Environments
 
|Year=2011
 
|Year=2011
|Booktitle=(to be published)
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|Month=Oktober
|Publisher=(to be published)
+
|Booktitle=Proceedings of the 3rd International Joint Conference on Computational Intelligence
 +
|Pages=90-102
 +
|Publisher=IEEE Computer Society
 
}}
 
}}
 
{{Publikation Details
 
{{Publikation Details
 
|Abstract=In this paper, a theoretical and experimental study of the influence of environments on the selection process
 
|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.
 
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.
|Download=Final-version.pdf,  
+
|Download=Final-version.pdf,
 
|Forschungsgruppe=Effiziente Algorithmen
 
|Forschungsgruppe=Effiziente Algorithmen
 
}}
 
}}
 
Java source code associated with this publication can be downloaded from this link: <tt>http://www.aifb.kit.edu/web/Datei:MarkovMatrixGenerator.zip</tt>
 
Java source code associated with this publication can be downloaded from this link: <tt>http://www.aifb.kit.edu/web/Datei:MarkovMatrixGenerator.zip</tt>

Aktuelle Version vom 15. November 2011, 15:02 Uhr


A Markov-Chain-Based Model for Success Prediction of Evolution in Complex Environments


A Markov-Chain-Based Model for Success Prediction of Evolution in Complex Environments



Published: 2011 Oktober

Buchtitel: Proceedings of the 3rd International Joint Conference on Computational Intelligence
Seiten: 90-102
Verlag: IEEE Computer Society

Referierte Veröffentlichung

BibTeX

Kurzfassung
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.

Download: Media:Final-version.pdf



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet


Java source code associated with this publication can be downloaded from this link: http://www.aifb.kit.edu/web/Datei:MarkovMatrixGenerator.zip