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A paper on parallel MonteCarlo Tree Search:
@inproceedings{bourki:inria00512854,
hal_id = {inria00512854},
url = {http://hal.inria.fr/inria00512854},
title = {{Scalability and Parallelization of MonteCarlo Tree Search}},
author = {Bourki, Amine and Chaslot, Guillaume and Coulm, Matthieu and Danjean, Vincent and Doghmen, Hassen and H{\'e}rault, Thomas and Hoock, JeanBaptiste and Rimmel, Arpad and Teytaud, Fabien and Teytaud, Olivier and Vayssi{\`e}re, Paul and Yu, Ziqin},
booktitle = {{The International Conference on Computers and Games 2010}},
address = {Kanazawa, Japon},
audience = {internationale },
collaboration = {Grid'5000 },
year = {2010},
pdf = {http://hal.inria.fr/inria00512854/PDF/newcluster.pdf},
}
And a paper on parallel optimization:
@inproceedings{teytaud:inria00369781,
hal_id = {inria00369781},
url = {http://hal.inria.fr/inria00369781},
title = {{On the parallel speedup of Estimation of Multivariate Normal Algorithm and Evolution Strategies}},
author = {Teytaud, Fabien and Teytaud, Olivier},
abstract = {{Motivated by parallel optimization, we experiment EDAlike adaptationrules in the case of $\lambda$ large. The rule we use, essentially based on estimation of multivariate normal algorithm, is (i) compliant with all families of distributions for which a density estimation algorithm exists (ii) simple (iii) parameterfree (iv) better than current rules in this framework of $\lambda$ large. The speedup as a function of $\lambda$ is consistent with theoretical bounds.}},
language = {Anglais},
affiliation = {Institut National de la Recherche en Informatique et en Automatique  INRIA FUTURS , UFR Sciences  Universit{\'e} ParisSud XI , TAO  INRIA Futurs , Laboratoire de Recherche en Informatique  LRI , TAO  INRIA Saclay  Ile de France},
booktitle = {{EvoNum (evostar workshop)}},
publisher = {springer},
address = {Tuebingen, Allemagne},
volume = {EvoNum},
audience = {internationale },
collaboration = {Grid'5000 },
year = {2009},
pdf = {http://hal.inria.fr/inria00369781/PDF/lambdaLarge.pdf},
}
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