Reformulation of constraint satisfaction problems for stochastic search

A computer-implemented method for solving a constraint satisfaction problem (CSP), which is defined by variables and constraints applicable to the variables, and which has states corresponding to respective sets of values of the variables. The method includes assigning cost functions to the constraints so that the states have respective costs determined by application of the cost functions to the respective sets of values of the variables, the respective costs defining a problem topography of the CSP having global extrema corresponding to solutions of the CSP. The constraints of the CSP are reformulated so as to perform at least one of increasing a density of the solutions in the problem topography and smoothing a gradient of the problem topography. One or more of the solutions of the CSP are found by applying a stochastic CSP solver to the reformulated constraints.