  In a field of research about general reasoning mechanisms, it is essential to
have appropriate benchmarks. Ideally, the benchmarks should reflect possible
applications of the developed technology. In AI Planning, researchers more and
more tend to draw their testing examples from the benchmark collections used in
the International Planning Competition (IPC). In the organization of (the
deterministic part of) the fourth IPC, IPC-4, the authors therefore invested
significant effort to create a useful set of benchmarks. They come from five
different (potential) real-world applications of planning: airport ground
traffic control, oil derivative transportation in pipeline networks,
model-checking safety properties, power supply restoration, and UMTS call
setup. Adapting and preparing such an application for use as a benchmark in the
IPC involves, at the time, inevitable (often drastic) simplifications, as well
as careful choice between, and engineering of, domain encodings. For the first
time in the IPC, we used compilations to formulate complex domain features in
simple languages such as STRIPS, rather than just dropping the more interesting
problem constraints in the simpler language subsets. The article explains and
discusses the five application domains and their adaptation to form the PDDL
test suites used in IPC-4. We summarize known theoretical results on structural
properties of the domains, regarding their computational complexity and
provable properties of their topology under the h+ function (an idealized
version of the relaxed plan heuristic). We present new (empirical) results
illuminating properties such as the quality of the most wide-spread heuristic
functions (planning graph, serial planning graph, and relaxed plan), the growth
of propositional representations over instance size, and the number of actions
available to achieve each fact; we discuss these data in conjunction with the
best results achieved by the different kinds of planners participating in
IPC-4.
