A Markov-Chain-Based Model for Success Prediction of Evolution in Complex Environments
Buchtitel: Proceedings of the 3rd International Joint Conference on Computational Intelligence
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.
Java source code associated with this publication can be downloaded from this link: http://www.aifb.kit.edu/web/Datei:MarkovMatrixGenerator.zip