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