I am happy to announce that the following paper has been accepted at the 17th International Conference on Computational Science (ICCS) to be held in Zürich, Switzerland on June 12-14. Title and authors: Title : Parallel Learning Portfolio-based solvers. Tarek Menour (1,3), Souheib Baarir(1,2,3). (1) Paris Ouest Nanterre la Défense University (2) LRDE, EPITA, Kremlin-Bicêtre, France (3) LIP6 Laboratory, CNRS UMR 7606, Paris, France. Abstract: Exploiting multi-core architectures is a way to tackle the CPU time consumption when solving SATisfiability (SAT) problems. Portfolio is one of the main techniques that implements this principle. It consists in making several solvers competing, on the same problem, and the winner will be the first that answers. In this work, we improved this technique by using a learning schema, namely the Exploration-Exploitation using Exponential weight (EXP3), that allows smart resource allocations. Our contribution is adapted to situations where we have to solve a bench of SAT instances issued from one or several sequence of problems. Our experiments show that our approach achieves good results in comparison with the state of the art solvers.