43 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
OASys: An AND/OR parallel logic programming system
The OASys (Or/And SYStem) is a software implementation designed for
AND/OR-parallel execution of logic programs. In order to combine these
two types of parallelism, OASys considers each alternative path as a
totally independent computation (leading to OR-parallelism) which
consists of a conjunction of determinate subgoals (leading to
AND-parallelism). This computation model is motivated by the need for
the elimination of communication between processing elements (PEs).
OASys aims towards a distributed memory architecture in which the PEs
performing the OR-parallel computation possess their own address space
while other simple processing units are assigned with AND-parallel
computation and share the same address space. OASys execution is based
on distributed scheduling which allows either recomputation of paths or
environment copying. We discuss in detail the OASys execution scheme and
we demonstrate OASys effectiveness by presenting the results obtained by
a prototype implementation, running on a network of workstations. The
results show that speedup obtained by AND/OR-parallelism is greater than
the speedups obtained by exploiting AND or OR-parallelism alone. In
addition, comparative performance measurements show that copying has a
minor advantage over recomputation. (C) 1999 Elsevier Science B.V. All
rights reserved