  We describe a duality mapping between STRIPS planning tasks. By exchanging
the initial and goal conditions, taking their respective complements, and
swapping for every action its precondition and delete list, one obtains for
every STRIPS task its dual version, which has a solution if and only if the
original does. This is proved by showing that the described transformation
essentially turns progression (forward search) into regression (backward
search) and vice versa.
  The duality sheds new light on STRIPS planning by allowing a transfer of
ideas from one search approach to the other. It can be used to construct new
algorithms from old ones, or (equivalently) to obtain new benchmarks from
existing ones. Experiments show that the dual versions of IPC benchmarks are in
general quite difficult for modern planners. This may be seen as a new
challenge. On the other hand, the cases where the dual versions are easier to
solve demonstrate that the duality can also be made useful in practice.

Artificial Intelligence