1,265 research outputs found
The GRT Planning System: Backward Heuristic Construction in Forward State-Space Planning
This paper presents GRT, a domain-independent heuristic planning system for
STRIPS worlds. GRT solves problems in two phases. In the pre-processing phase,
it estimates the distance between each fact and the goals of the problem, in a
backward direction. Then, in the search phase, these estimates are used in
order to further estimate the distance between each intermediate state and the
goals, guiding so the search process in a forward direction and on a best-first
basis. The paper presents the benefits from the adoption of opposite directions
between the preprocessing and the search phases, discusses some difficulties
that arise in the pre-processing phase and introduces techniques to cope with
them. Moreover, it presents several methods of improving the efficiency of the
heuristic, by enriching the representation and by reducing the size of the
problem. Finally, a method of overcoming local optimal states, based on domain
axioms, is proposed. According to it, difficult problems are decomposed into
easier sub-problems that have to be solved sequentially. The performance
results from various domains, including those of the recent planning
competitions, show that GRT is among the fastest planners
Cooperation between Top-Down and Bottom-Up Theorem Provers
Top-down and bottom-up theorem proving approaches each have specific
advantages and disadvantages. Bottom-up provers profit from strong redundancy
control but suffer from the lack of goal-orientation, whereas top-down provers
are goal-oriented but often have weak calculi when their proof lengths are
considered. In order to integrate both approaches, we try to achieve
cooperation between a top-down and a bottom-up prover in two different ways:
The first technique aims at supporting a bottom-up with a top-down prover. A
top-down prover generates subgoal clauses, they are then processed by a
bottom-up prover. The second technique deals with the use of bottom-up
generated lemmas in a top-down prover. We apply our concept to the areas of
model elimination and superposition. We discuss the ability of our techniques
to shorten proofs as well as to reorder the search space in an appropriate
manner. Furthermore, in order to identify subgoal clauses and lemmas which are
actually relevant for the proof task, we develop methods for a relevancy-based
filtering. Experiments with the provers SETHEO and SPASS performed in the
problem library TPTP reveal the high potential of our cooperation approaches
Abduction in Well-Founded Semantics and Generalized Stable Models
Abductive logic programming offers a formalism to declaratively express and
solve problems in areas such as diagnosis, planning, belief revision and
hypothetical reasoning. Tabled logic programming offers a computational
mechanism that provides a level of declarativity superior to that of Prolog,
and which has supported successful applications in fields such as parsing,
program analysis, and model checking. In this paper we show how to use tabled
logic programming to evaluate queries to abductive frameworks with integrity
constraints when these frameworks contain both default and explicit negation.
The result is the ability to compute abduction over well-founded semantics with
explicit negation and answer sets. Our approach consists of a transformation
and an evaluation method. The transformation adjoins to each objective literal
in a program, an objective literal along with rules that ensure
that will be true if and only if is false. We call the resulting
program a {\em dual} program. The evaluation method, \wfsmeth, then operates on
the dual program. \wfsmeth{} is sound and complete for evaluating queries to
abductive frameworks whose entailment method is based on either the
well-founded semantics with explicit negation, or on answer sets. Further,
\wfsmeth{} is asymptotically as efficient as any known method for either class
of problems. In addition, when abduction is not desired, \wfsmeth{} operating
on a dual program provides a novel tabling method for evaluating queries to
ground extended programs whose complexity and termination properties are
similar to those of the best tabling methods for the well-founded semantics. A
publicly available meta-interpreter has been developed for \wfsmeth{} using the
XSB system.Comment: 48 pages; To appear in Theory and Practice in Logic Programmin
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