Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F18%3A00326672" target="_blank" >RIV/68407700:21340/18:00326672 - isvavai.cz</a>

Result on the web

<a href="http://ceur-ws.org/Vol-2203/72.pdf" target="_blank" >http://ceur-ws.org/Vol-2203/72.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy

Original language description

Many real-world problems belong to the area of continuous black-box optimization, where evolutionary optimizers have become very popular inspite of the fact that such optimizers require a great amount of real-world fitness function evaluations, which can be very expensive or time-consuming. Hence, regression surrogate models are often utilized to evaluate some points instead of the fitness function. The Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy (DTS-CMA-ES) is a surrogate-assisted version of the state-of-the-art continuous black-box optimizer CMA-ES using Gausssian processes as a surrogate model to predict the whole distribution of the fitness function. In this paper, the DTS-CMA-ES is studied in connection with the boosted regression forest, another regression model capable to estimate the distribution. Results of testing regression forest and Gaussian processes, the former in 20 different settings, as a surrogate models in the DTS-CMA-ES on the set of noiseless benchmarks are reported.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 18th Conference Information Technologies - Applications and Theory (ITAT 2018)

ISBN

9781727267198

ISSN

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e-ISSN

1613-0073

Number of pages

8

Pages from-to

72-79

Publisher name

CEUR Workshop Proceedings

Place of publication

Aachen

Event location

Krompachy

Event date

Sep 21, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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