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.