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This paper presents a survey of artificial intelligence techniques that have hitherto been applied to adaptive autoreclosure, namely artificial neural networks, fuzzy logic and genetic algorithms. The aim is to discern the most suitable techniques for applying adaptive autoreclosure to systems with high penetrations of wind power. Traditionally, adaptive autoreclosure schemes have been implemented using a combination of signal processing and artificial neural networks. A number of variations on this conventional approach are proposed in this paper. Qualitative discussion shows that in theory, a combination of the examined AI techniques will provide the most robust methodology, combining the strengths of each technique whilst minimizing weaknesses.