Fitness importance for online evolution

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Fitness importance for online evolution
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 manipulate 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 on a collection of physical wireless sensor network devices. We also describe the In situ Distributed Genetic Programming (IDGP) framework which has been developed for online evolution of logic on resource-constrained computing devices and demonstrate how FI can be used with the framework in order to achieve a dynamic balance of learning and performing. Categories and Subject Descriptors I.2.2 [Computing Methodologies]: Artificial Intelligence-Automatic Programming [Program synthesis] General Terms Algorithms, Design Keywords Late Breaking Abstract, Fitness, Obje...
Philip Valencia, Raja Jurdak, Peter Lindsay
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Authors Philip Valencia, Raja Jurdak, Peter Lindsay
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