|dc.description.abstract||In applications of HTN planning, repeated problems have arisen from the
lack of correspondence between HTN tasks and classical-planning goals.
We describe these problems and provide a new Hierarchical Goal Network
(HGN) planning formalism that overcomes them. HGN tasks have syntax and
semantics analogous to classical planning problems, and this has several
benefits: HGN methods can be significantly simpler to write than HTN
methods, there is a clear criterion for whether the HGN methods are
correct, and classical-planning heuristic functions can be adapted for
use in HGN planning.
We define the HGN formalism, illustrate how to prove correctness of HGN
methods, provide a planning algorithm called GNP (Goal Network Planner),
and present experimental results showing that GNP’s performance compares
favorably to that of SHOP2. We provide a planning-graph heuristic for
optional use in GNP, and give experimental results showing the kinds of
situations in which it helps or hurts GNP’s performance.||en_US