Experiences in solving constraint relaxation networks with Boltzmann Machines
Earlier, Guesgen and Hertzberg have given a theoretical description of how to implement constraint relaxation in terms of combinatorial optimization using the concept of Boltzmann Machines. This paper sketches some lessons that an implementation of this idea has taught us about how to tailor the translation from constraint networks to Boltzmann Machines such that the resulting implementation be efficient.
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