TY - GEN
T1 - On multiplicative noise models for stochastic search
AU - Jebalia, Mohamed
AU - Auger, Anne
PY - 2008/11/26
Y1 - 2008/11/26
N2 - In this paper we investigate multiplicative noise models in the context of continuous optimization. We illustrate how some intrinsic properties of the noise model imply the failure of reasonable search algorithms for locating the optimum of the noiseless part of the objective function. Those findings are rigorously investigated on the (1 + 1)-ES for the minimization of the noisy sphere function. Assuming a lower bound on the support of the noise distribution, we prove that the (1 + 1)-ES diverges when the lower bound allows to sample negative fitness with positive probability and converges in the opposite case. We provide a discussion on the practical applications and non applications of those outcomes and explain the differences with previous results obtained in the limit of infinite search-space dimensionality.
AB - In this paper we investigate multiplicative noise models in the context of continuous optimization. We illustrate how some intrinsic properties of the noise model imply the failure of reasonable search algorithms for locating the optimum of the noiseless part of the objective function. Those findings are rigorously investigated on the (1 + 1)-ES for the minimization of the noisy sphere function. Assuming a lower bound on the support of the noise distribution, we prove that the (1 + 1)-ES diverges when the lower bound allows to sample negative fitness with positive probability and converges in the opposite case. We provide a discussion on the practical applications and non applications of those outcomes and explain the differences with previous results obtained in the limit of infinite search-space dimensionality.
UR - https://www.scopus.com/pages/publications/56449105350
U2 - 10.1007/978-3-540-87700-4_6
DO - 10.1007/978-3-540-87700-4_6
M3 - Conference contribution
AN - SCOPUS:56449105350
SN - 3540876995
SN - 9783540876991
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 52
EP - 61
BT - Parallel Problem Solving from Nature - PPSN X - 10th International Conference, Proceedings
T2 - 10th International Conference on Parallel Problem Solving from Nature, PPSN X
Y2 - 13 September 2008 through 17 September 2008
ER -