@inproceedings{eyerich:ecai-2012,
   author = "Patrick Eyerich",
   title = "Preferring Properly: Increasing Coverage while Maintaining
     Quality in Anytime Temporal Planning",
   booktitle = "Proceedings of the 20th European Conference on
                  Artificial Intelligence (ECAI)",
   month = "august",
   year = "2012",
   publisher = "IOS Press",
   abstract = "Temporal Fast Downward (TFD) is a successful temporal
                  planning system that is capable of dealing with
                  numerical values. Rather than decoupling action
                  selection from scheduling, it searches directly in
                  the space of time-stamped states, an approach that
                  has shown to produce plans of high quality at the
                  price of coverage. To increase coverage, TFD
                  incorporates deferred evaluation and preferred
                  operators, two search techniques that usually
                  decrease the number of heuristic calculations by a
                  large amount. However, the current definition of
                  preferred operators offers only limited guidance in
                  problems where heuristic estimates are weak or where
                  subgoals require the execution of mutex
                  operators. In this paper, we present novel methods
                  for refinement of this definition and show how to
                  combine the diverse strengths of different sets of
                  preferred operators using a restarting procedure
                  incorporated into a multi-queue best-first
                  search. These techniques improve TFD's coverage
                  drastically and preserve the average solution
                  quality, leading to a system that solves more
                  problems than each of the competitors of the
                  temporal satisficing track of IPC 2011 and clearly
                  outperforms all of them in terms of IPC score."
}