Počet záznamů: 1
Evolutionary optimization with active learning of surrogate models and fixed evaluation batch size
- 1.
SYSNO ASEP 0384885 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Evolutionary optimization with active learning of surrogate models and fixed evaluation batch size Tvůrce(i) Charypar, V. (CZ)
Holeňa, Martin (UIVT-O) SAI, RIDZdroj.dok. Information Technologies - Applications and Theory. - Seňa : PONT s.r.o., 2012 / Horváth T. - ISBN 978-80-971144-0-4 Rozsah stran s. 33-40 Poč.str. 8 s. Forma vydání Online - E Akce ITAT 2012. Conference on Theory and Practice of Information Technologies Datum konání 17.09.2012-21.09.2012 Místo konání Ždiar Země SK - Slovensko Typ akce EUR Jazyk dok. eng - angličtina Země vyd. SK - Slovensko Klíč. slova evolutionary optimization ; fitness evaluation ; surrogate modelling ; Gaussian process ; active learning Vědní obor RIV IN - Informatika CEP GA201/08/0802 GA ČR - Grantová agentura ČR Institucionální podpora UIVT-O - RVO:67985807 EID SCOPUS 84873909264 Anotace Evolutionary optimization is often applied to problems, where simulations or experiments used as the fitness function are expensive to run. In such cases, surrogate models are used to reduce the number of fitness evaluations. Some of the problems also require a fixed size batch of solutions to be evaluated at a time. Traditional methods of selecting individuals for true evaluation to improve the surrogate model either require individual points to be evaluated, or couple the batch size with the EA generation size. We propose a queue based method for individual selection based on active learning of a kriging model. Individuals are selected using the confidence intervals predicted by the model, added to a queue and evaluated once the queue length reaches the batch size. The method was tested on several standard benchmark problems. Results show that the proposed algorithm is able to achieve a solution using significantly less evaluations of the true fitness function. The effect of the batc Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2013
Počet záznamů: 1