An introduction to genetic algorithms
An introduction to genetic algorithms
The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
An Incremental Self-Deployment Algorithm for Mobile Sensor Networks
Autonomous Robots
The Effects of Representational Bias on Collaboration Methods in Cooperative Coevolution
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
An Efficient Coevolutionary Algorithm Using Dynamic Species Control
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 03
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We propose an innovative cooperative co-evolutionary computation framework, Dynamic Cooperative Coevolution (DCC), which provides dynamic coupling of neighboring species for the fitness evaluation of individuals. One feature of DCC is the utilization of local fitness to achieve a global optimum, which makes it possible for co-evolutionary algorithms to be applied in localized distributed environments, such as network computing. This work is motivated by our interest in autonomous sensor deployment, where a sensor can only communicate with those within a limited range. Our experiments show that DCC is effective in obtaining good solutions under such distributed and localized conditions.