Work

Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy

Year: 2012

Type: conference-paper

Abstract: This paper presents a novel mechanism to adapt surrogate-assisted population-based algorithms. This mechanism is applied to ACM-ES, a recently proposed surrogate-assisted variant of CMA-ES. The resulting algorithm, s*ACM-ES, adjusts online the lifelength of the current surrogate model (the number of CMA-ES generations before learning a new surrogate) and the surrogate hyper-parameters.

Source: Genetic and Evolutionary Computation Conference (GECCO)

DOI: 10.1145/2330163.2330210

Authors: Ilya Loshchilov, Marc Schoenauer, Michele Sebag

Institutions: Institut national de recherche en sciences et technologies du numérique, Université Paris-Sud, Centre National de la Recherche Scientifique

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2141867233

FWCI: 5.151

Cites: 31

Cited by: 86

Related to: 10