[Diversity search] PSE and stochasticity

[JusteRaimbault]

Exploring a highly stochastic model with PSE lead some of us to a questioning on assumptions for a "reasonable" use of PSE regarding stochastic variability of indicators: from what I understood and what seems to be the consensus, probability distributions for a given parameter value should be relatively "narrow" (i.e. with a relatively low standard deviation and no fat tail) and the algorithm works with aggregates (generally medians), so solutions with few replications should be removed in the end. What about a possible application to highly stochastic models, e.g. with power law distributions, or when noise is significantly higher than variations due to parameters ? Should we investigate other types of algorithms specific to that purpose ? I have in mind a cloning algorithm for large deviation functions ( arxiv:0811.1041 ) for example, may be worth to look into that and to see to what extent similar stuff could be used in such a highly noisy context.