Distributed genetic evolution in WSN
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
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To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be used to dynamically bias the population composition in order to vary the instantaneous system performance at a tradeoff to learning capability. The effect of FI is demonstrated on a simple light-sensing and light-actuating optimisation problem running on multiple wireless sensor network devices. We also describe how FI can be used with the In situ Distributed Genetic Programming (IDGP) framework to balance learning and performing for resource-constrained computing devices which evolve their logic continuously.