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Automated Planning
book

Automated Planning

by Malik Ghallab, Dana Nau, Paolo Traverso
May 2004
Intermediate to advanced content levelIntermediate to advanced
635 pages
19h 46m
English
Morgan Kaufmann
Content preview from Automated Planning
206 Chapter 9 Heuristics in Planning
with respect to an a priori given upper bound. However, experience shows that h
1
is not as informative as h
0
. It usually leads to a much less focused search.
The idea behind h
1
can be extended in order to produce a more informative
heuristic that is still admissible. Instead of considering that the distance to a set g is
the maximum distance to a proposition p g , we estimate it to be the maximum
distance to a pair of propositions {p, q}∈g . This new estimate
2
is defined accord-
ing to the three following recursive equations (in addition to the termination cases
that remain as in Formulas 9.1):
2
(s, p) = min
a
{1 +
2
(s, precond(a)) | p effects
+
(a)}
2
(s, {p, q}) = min{
min
a
{1 +
2
(s, precond(a)) |{p, q}⊆effects ...
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Publisher Resources

ISBN: 9781558608566