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The "Divide and Concur" (DC) algorithm, recently introduced by Gravel and Elser, can be considered a competitor to the belief propagation (BP) algorithm, in that both algorithms can be applied to a wide variety of constraint satisfaction, optimization, and probabilistic inference problems. We show that DC can be interpreted as a message-passing algorithm on a constraint graph, which helps make the comparison with BP more clear. The "difference-map" dynamics of the DC algorithm enables it toarXiv:1001.1730v1 fatcat:fnh7hx7vqzbjpjwzdkbv3ijnoe