Resource-Based Fitness Sharing
This paper introduces a new algorithm for sharing to induce niching and speciation. Resource-based fitness sharing is a compromise between the very natural method of resource sharing and the practical technique of fitness sharing. Fitness sharing was meant to simulate resource sharing for function optimization problems, in which there are no explicit resources to share. Fitness sharing therefore cannot resolve resource-defined niches as can resource sharing. However, selection operators seem to have great difficulty handling the non-linear interactions among shared fitnesses under “natural resource sharing”. To obtain the benefits of both methods, we propose a sharing function that utilizes actual resources but in a form similar to that of fitness sharing, resulting in a set of linear equations for equilibrium, and hence much simpler dynamics under selection. The superiority of this compromise is demonstrated on a resource-coverage problem.
KeywordsResource Sharing Learn Classifier System Corner Effect Initial Random Population Function Optimization Problem
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