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The hessian estimation evolution strategy

Authors :
Glasmachers, Tobias
Krause, Oswin
Bäck, Thomas
Preuss, Mike
Deutz, André
Emmerich, Michael
Wang, Hao
Doerr, Carola
Trautmann, Heike
Source :
Glasmachers, T & Krause, O 2020, The hessian estimation evolution strategy . in T Bäck, M Preuss, A Deutz, M Emmerich, H Wang, C Doerr & H Trautmann (eds), Parallel Problem Solving from Nature – PPSN XVI-16th International Conference, PPSN 2020, Proceedings . Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12269 LNCS, pp. 597-609, 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, Leiden, Netherlands, 05/09/2020 . https://doi.org/10.1007/978-3-030-58112-1_41
Publication Year :
2020
Publisher :
Springer, 2020.

Abstract

We present a novel black box optimization algorithm called Hessian Estimation Evolution Strategy. The algorithm updates the covariance matrix of its sampling distribution by directly estimating the curvature of the objective function. This algorithm design is targeted at twice continuously differentiable problems. For this, we extend the cumulative step-size adaptation algorithm of the CMA-ES to mirrored sampling. We demonstrate that our approach to covariance matrix adaptation is efficient by evaluating it on the BBOB/COCO testbed. We also show that the algorithm is surprisingly robust when its core assumption of a twice continuously differentiable objective function is violated. The approach yields a new evolution strategy with competitive performance, and at the same time it also offers an interesting alternative to the usual covariance matrix update mechanism.

Details

Language :
English
Database :
OpenAIRE
Journal :
Glasmachers, T & Krause, O 2020, The hessian estimation evolution strategy . in T Bäck, M Preuss, A Deutz, M Emmerich, H Wang, C Doerr & H Trautmann (eds), Parallel Problem Solving from Nature – PPSN XVI-16th International Conference, PPSN 2020, Proceedings . Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12269 LNCS, pp. 597-609, 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, Leiden, Netherlands, 05/09/2020 . https://doi.org/10.1007/978-3-030-58112-1_41
Accession number :
edsair.od......2751..cabbdd1180154132025c3a58f8755c48
Full Text :
https://doi.org/10.1007/978-3-030-58112-1_41