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KOBLIHA, M. SCHWARZ, J. OČENÁŠEK, J.
Original Title
Bayesian Optimization Algorithm in Dynamic Environment
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
This paper is an experimental study investigating the capability of Bayesian optimization algorithms to solve dynamic problems. We tested the performance of two types of Bayesian optimization algorithms - Mixed continuous-discrete Bayesian Optimization Algorithm (MBOA), and Adaptive Mixed Bayesian Optimization Algorithm (AMBOA). We have compared the behaviour of both algorithms on a simple dynamic environment defined as a time-varying function with predefined parameters.
Keywords
Dynamic environment, Estimation of Distribution Algorithms, Bayesian Optimization Algorithms, variance adaptation, time-varying test function
Authors
KOBLIHA, M.; SCHWARZ, J.; OČENÁŠEK, J.
RIV year
2005
Released
15. 6. 2005
Publisher
Faculty of Mechanical Engineering BUT
Location
Brno, CZ
ISBN
80-214-2961-5
Book
Mendel 2005 11th Internacional Conference on Soft Computing
Pages from
15
Pages to
20
Pages count
6
BibTex
@inproceedings{BUT21527, author="Miloš {Kobliha} and Josef {Schwarz} and Jiří {Očenášek}", title="Bayesian Optimization Algorithm in Dynamic Environment", booktitle="Mendel 2005 11th Internacional Conference on Soft Computing", year="2005", pages="15--20", publisher="Faculty of Mechanical Engineering BUT", address="Brno, CZ", isbn="80-214-2961-5" }