  Planning is a notoriously difficult computational problem of high worst-case
complexity. Researchers have been investing significant efforts to develop
heuristics or restrictions to make planning practically feasible. Case-based
planning is a heuristic approach where one tries to reuse previous experience
when solving similar problems in order to avoid some of the planning effort.
Plan reuse may offer an interesting alternative to plan generation in some
settings.
  We provide theoretical results that identify situations in which plan reuse
is provably tractable. We perform our analysis in the framework of
parameterized complexity, which supports a rigorous worst-case complexity
analysis that takes structural properties of the input into account in terms of
parameters. A central notion of parameterized complexity is fixed-parameter
tractability which extends the classical notion of polynomial-time tractability
by utilizing the effect of structural properties of the problem input.
  We draw a detailed map of the parameterized complexity landscape of several
variants of problems that arise in the context of case-based planning. In
particular, we consider the problem of reusing an existing plan, imposing
various restrictions in terms of parameters, such as the number of steps that
can be added to the existing plan to turn it into a solution of the planning
instance at hand.

Artificial Intelligence;Computational Complexity