Consistent singleton models of a temporal constraint network

The authors provide an efficient algorithm that obtains consistent singleton models of a temporal network by applying a forward pruning technique for the search space. It is important that an intelligent system should be able to capture the notion of time and be able to reason about it. The primitives to represent times are points and intervals. An interval representation for time is used. Obtaining all the satisfiable models of a constraint network. even if the constraints are limited to the pointisable subset of interval relations, takes exponential time in the worst case. Therefore, any success in this area depends on efficient pruning techniques and heuristics. A technique based on pruning the search space is described