  Practically all of the planning research is limited to states represented in
terms of Boolean and numeric state variables. Many practical problems, for
example, planning inside complex software systems, require far more complex
data types, and even real-world planning in many cases requires concepts such
as sets of objects, which are not convenient to express in modeling languages
with scalar types only. In this work, we investigate a modeling language for
complex software systems, which supports complex data types such as sets,
arrays, records, and unions. We give a reduction of a broad range of complex
data types and their operations to Boolean logic, and then map this
representation further to PDDL to be used with domain-independent PDDL
planners. We evaluate the practicality of this approach, and provide solutions
to some of the issues that arise in the PDDL translation.
