Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Reward allotment in an event-driven hybrid learning classifier system for online soccer games
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Viral infection + tropism for improving small population performance under noisy environment
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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In this paper we report on the effect of viral infection with tropism on the formation of building blocks in genetic operations. In previous research, we applied genetic algorithms to the analysis of time-series signals with noise. We demonstrated the possibility of reducing the number of required entities and improving the rate of convergence when searching for a solution by having some of the host chromosomes harbor viruses with a tropism function. Here, we simulate problems having both multimodality and deceptiveness features and problems that include noise as test functions, and show that viral infection with tropism can increase the proportion of building blocks in the population when it cannot be assumed that a necessary and sufficient number of entities are available to find a solution. We show that this capability is especially noticeable in problems that include noise.