  Many decision-making approaches rely on the exploration of solution spaces
with regards to specified criteria. However, in complex environments,
brute-force exploration strategies are usually not feasible. As an alternative,
we propose the combination of an exploration task's vertical sub-division into
layers representing different sequentially interdependent sub-problems of the
paramount problem and a horizontal sub-division into self-sustained solution
sub-spaces. In this paper, we present a universal methodology for the
intelligent exploration of solution spaces and derive a use-case specific
example from the field of reconfiguration management in industry 4.0.
