Thanks Romain, it answers my question but creates a lot more since it's not
working the way I thought it was...! But I think I'm gonna read up about
the steady state version of GA before asking everything here.

Just one question: is it possible to use the generational version of GA in
openmole? I tried to use nsga2 with a termination parameter but it didn't
work.

Hélène

2017-06-01 15:15 GMT+02:00 Romain Reuillon <[email protected]>:

> Hi Helene,
>
>
> Le 01/06/2017 à 14:50, Hélène Arduin a écrit :
>
> Hi,
>
> Thank you Alberto for the explanation!
>
> Anyone on the parallelism parameter? I don't understand if the parallel
> generations are drawn simultaneously, computed and then regrouped before
> moving to the next ones, or if they are completely independent, or
> something else?
>
>
> the genetic algorithm are implement in there steady state version (as
> opposed to generational). It means that you'll have a pool of n concurent
> evaluations (running on different nodes). A soon a an evaluation is
> terminated the result is merged to the global population and an new
> evaluation (or job) is created.
>
> Does it answer your question?
>
> Romain
>
>
> Hélène
>
>
> _______________________________________________
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>
>
>


-- 
Hélène Arduin
PhD student
Biostatistics, Biomathematics, Pharmaco-Epidemiology and Infectious Diseases
Inserm UMR1181 / Université Versailles Saint-Quentin en Yvelines / Institut
Pasteur

25 rue du Docteur Roux
75724 Paris Cedex 15, France
Tél : +33 (0)1 44 38 91 38

http://b2phi.inserm.fr
https://research.pasteur.fr/en/team/pharmacoepidemiology-and-infectious-diseases
<https://research.pasteur.fr/en/team/pharmacopepidemiology-and-infectious-diseases>
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