  In this paper we propose a family of algorithms combining tree-clustering
with conditioning that trade space for time. Such algorithms are useful for
reasoning in probabilistic and deterministic networks as well as for
accomplishing optimization tasks. By analyzing the problem structure it will be
possible to select from a spectrum the algorithm that best meets a given
time-space specification.
