An algorithm is presented for determining the values which simultaneously satisfy a set of relations, or constraints, involving different subsets of n variables. The relations are represented in a series of constraint networks, which ultimately contain a node for every subset of the n variables. Constraints may be propagated through such networks in (potentially) parallel fashion to determine the values which simultaneously satisfy all the constraints. The iterated constraint propagation serves to mitigate combinatorial explosion. Applications in scene analysis, graph theory, and backtrack search are provided.
