  In this work an iterative algorithm based on unsupervised learning is
presented, specifically on a Restricted Boltzmann Machine (RBM) to solve a
perfect matching problem on a bipartite weighted graph. Iteratively is
calculated the weights $w_{ij}$ and the bias parameters $\theta = ( a_i, b_j) $
that maximize the energy function and assignment element $i$ to element $j$. An
application of real problem is presented to show the potentiality of this
algorithm.
