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Extending the "Open-Closed Principle" to Automated Algorithm Configuration
2018
Evolutionary Computation
Metaheuristics are an effective and diverse class of optimization algorithms: a means of obtaining solutions of acceptable quality for otherwise intractable problems. The selection, construction, and configuration of a metaheuristic for a given problem has historically been a manually intensive process based on experience, experimentation, and reasoning by metaphor. More recently, there has been interest. In this paper, we identify shared state as the inhibitor of greater automation in
doi:10.1162/evco_a_00245
fatcat:v4643lke6jd5bamqkqgaib6x2i