Suspending and Resuming Computations in Engines for SLG Evaluation

Castro, Luís Fernando; Swift, Terrance; Warren, David S.

doi:10.1007/3-540-45587-6_21

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…We tested SLGAD on some synthetic problems that were used as benchmarks for SLG [7,11]: win, ranc and lanc. win is an implementation of the stalemate game and contains the clause win(X) : 0.8 : −move(X, Y ), ¬win(Y ).…”

Section: Methodsmentioning

confidence: 99%

Inference with Logic Programs with Annotated Disjunctions under the Well Founded Semantics

Riguzzi

2008

Logic Programming

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Logic Programs with Annotated Disjunctions (LPADs) allow to express probabilistic information in logic programming. The semantics of an LPAD is given in terms of well founded models of the normal logic programs obtained by selecting one disjunct from each ground LPAD clause. The paper presents SLGAD resolution that computes the (conditional) probability of a ground query from an LPAD and is based on SLG resolution for normal logic programs. SLGAD is evaluated on classical benchmarks for well founded semantics inference algorithms, namely the stalemate game and the ancestor relation. SLGAD is compared with Cilog2 and SLDNFAD, an algorithm based on SLDNF, on the programs that are modularly acyclic. The results show that SLGAD deals correctly with cyclic programs and, even if it is more expensive than SLDNFAD on problems where SLDNFAD succeeds, is faster than Cilog2 when the query is true in an exponential number of instances.

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Section: Methodsmentioning

confidence: 99%

Inference with Logic Programs with Annotated Disjunctions under the Well Founded Semantics

Riguzzi

2008

Logic Programming

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“…One approach is that the SLG-WAM modifies its choice point management to be like CHAT's: have a stack organization for its choice points rather than a cactus stack. Indeed this is possible and such an implementation has already been described in [1]. Then the algorithm of Figure 8 is directly applicable.…”

Section: Jet Pruningmentioning

confidence: 95%

Just enough tabling

Sagonas

Stuckey

2004

Proceedings of the 6th ACM SIGPLAN International Conference on Principles and Practice of Declarative Programming

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We introduce just enough tabling (JET), a mechanism to suspend and resume the tabled execution of logic programs at an arbitrary point. In particular, JET allows pruning of tabled logic programs to be performed without resorting to any recomputation. We discuss issues that are involved in supporting pruning in tabled resolution, how re-execution of tabled computations which were previously pruned can be avoided, and we describe the implementation of such a scheme based on an abstract machine like CHAT, which implements the suspension/resumption support that tabling requires through a combination of freezing and copying of execution states of suspended computations. Properties of just enough tabling and possible uses of the JET mechanism in a tabling system are also briefly discussed.

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“…Ciao Prolog implements a different strategy, called CHAT (Demoen and Sagonas 1999), which suspends by copying (part of) a computation path from the WAM stacks to a separate area of memory, and resumes by copying the computation path back into the WAM stacks. CHAT can thus be thought of as an approach based on copying rather than one based on sharing as with the SLG-WAM approach (performance analysis in Castro et al (2002) found the sharing approach to be superior for many tabled programs). B-Prolog uses a still different approach, called linear tabling (Zhou and Sato 2003), which rederives a suspended computation path rather than saving the suspended path in trail frames or in a separate CHAT area.…”

Section: Implementation Aspectsmentioning

confidence: 99%

XSB: Extending Prolog with Tabled Logic Programming

Swift¹,

Warren²

2011

Theory and Practice of Logic Programming

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144

128

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The paradigm of Tabled Logic Programming (TLP) is now supported by a number of Prolog systems, including XSB, YAP Prolog, B-Prolog, Mercury, ALS, and Ciao. The reasons for this are partly theoretical: tabling ensures termination and optimal known complexity for queries to a large class of programs. However, the overriding reasons are practical. TLP allows sophisticated programs to be written concisely and efficiently, especially when mechanisms such as tabled negation and call and answer subsumption are supported. As a result, TLP has now been used in a variety of applications from program analysis to querying over the semantic web. This paper provides a survey of TLP and its applications as implemented in the XSB Prolog, along with discussion of how XSB supports tabling with dynamically changing code, and in a multi-threaded environment.

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Suspending and Resuming Computations in Engines for SLG Evaluation

Cited by 6 publications

References 12 publications

Inference with Logic Programs with Annotated Disjunctions under the Well Founded Semantics

Inference with Logic Programs with Annotated Disjunctions under the Well Founded Semantics

Just enough tabling

XSB: Extending Prolog with Tabled Logic Programming

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