We introduce an algorithmic decision process for multialternative choice, the Neural Metropolis Algorithm, that combines binary comparisons and Markovian exploration. We show that a stochastic version of transitivity, a basic tenet of rationality, makes this algorithm value-based. In so doing, we extend to decision procedures some classic stochastic choice notions.