K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Proceedings of Joint International Conference and Symposium on Logic Programming, pages 274-289, Bonn, Germany, September 1996. The MIT Press.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... which model such forms of reasoning (see [11, 6, 1, 17] for overviews) these logics have been applied to various application problems like reasoning about action, diagnosis, legal reasoning and the like, and in the meantime serious systems implementing subsets of the logics are around, e.g. XSB [16], smodels [12] or dlv [10] In the formalisms developed so far defeasible conclusions are defined on the basis of a distinction between what is certainly true and what is true by default. Some systems use more fine grained distinctions, based on rankings or arbitrary priorities among the default ....

Sagonas, K., Swift, T. and David S. Warren. An Abstract Machine for Computing the Well-Founded Semantics. In Proceedings of the Joint International Conference and Symposium on Logic Programming Bonn, Germany, pages 274--288,MIT Press, 1996

....and often mentioned advantage of virtually all bottom up model generation procedures over Prolog. XSB Prolog. One of the view programming languages that works top down (as Prolog) and that has built in loop checking capabilities (as bottom up model generation procedures) is XSB Prolog [SSW00] XSB Prolog supports query answering wrt. the well founded semantics for normal logic programs [VGRS91] At the heart of XSB Prolog is the so called tabling device that stores solutions (instantiations) of goals as soon as computed. Based on tabling, it is even possible to compute extensions of ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming, 2000. To Appear.

....and often mentioned advantage of virtually all bottom up model generation procedures over Prolog. XSB Prolog. One of the view programming languages that works top down (as Prolog) and that has built in loop checking capabilities (as bottom up model generation procedures) is XSB Prolog [SSW00] XSB Prolog supports query answering wrt. the well founded semantics for normal logic programs [VGRS91] At the heart of XSB Prolog is the so called tabling device that stores solutions (instantiations) of goals as soon as computed. Based on tabling, it is even possible to compute extensions of ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming, 2000. To Appear.

....than the best systems) It is free and is available by anonymous ftp from URL:ftp: ftp.cs.sunysb.edu pub XSB . This is the first time that a negation different from negation asfinite failure (well founded semantics) has been incorporated into a complete PROLOG system. We refer the reader to [31, 33, 34, 77] for more detailed information. SLG resolution is very procedural in nature because it is based on tabling techniques. Roughly, given a query and a program it first computes a residual program with respect to the query. Under some assumptions (boundedterm size property and similar concepts) which ....

....recursively during the whole search for stable models. This keeps the search space substantially smaller in smodels. These results lead to an interesting idea of combining SLG resolution and our method for computing stable models of ground programs. An implementation of SLG resolution, like XSB [77], could be used for implementing the well founded semantics and for computing the residual program for a query. When continuing towards the stable model semantics, our system could be employed starting from the ground residual program. However, there is a difference when using our grounding ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the Well-Founded semantics. In Michael Maher, editor, Proceedings of Joint International Conference and Symposium on Logic Programming, pages 274--288. The MIT Press, 1996.

....[NS96] Notice that the SLG system can handle the stable model semantics also for non ground programs provided that the resulting residual program is nite. This seems to be a promising approach for non ground programs: given a query, use an ecient implementation of SLGresolution like XSB [SSW96] and compute the residual program and then use another method, like the one presented in this section, for evaluating the query with respect to stable models on the basis of the residual program. However, the use of the residual program can lead to unsound results: the stable models of the ....

K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 274-288, Bonn, Germany, September 1996. The MIT Press.

....earlier at the end of section 5 these could be integrated by means of some loop checking techniques. A particularly e ective computation of the well founded model semantics, employing various forms of loop checking that may be usefully integrated into our procedures, is SLG resolution studied in [7, 8, 41, 38]. Here, the technique of tabling is employed to handle positive loops (like the one in example 54) and the technique of delaying is used to handle negative loops (like the ones in examples 4, 7 and 12) These techniques also allow to avoid repetitions in the resolution of goals. SLG is sound and ....

....propositional form. Despite these di erences in approach, it would be interesting to investigate to what extent methods adopted in these works could be integrated into our proof procedures for argumentation in order to improve their eciency. Similarly, tabling and other techniques introduced in [6, 7, 8, 41, 38] again for the ecient computation of the well founded (and stable model) semantics might be useful in developing e ective implementations of our proof procedures. Other argumentation semantics for LP have been proposed, e.g. 1] The use of the computational model given in our paper for ....

K. Sagonas, T. Swift and D.S. Warren. An abstract machine for computing the well-founded semantics. JICSLP'96, Bonn, Germany (1996), MIT Press (M. Maher ed.) 274-289

....rather than over a single SLD tree. The data structures and instruction set used by the SLG WAM for definite programs are described by Swift and Warren in [SW94a] and extensions to handle normal logic programs according to the well founded semantics [vRS91] are discussed by Sagonas et al. in [SSW96a] and by Sagonas in [Sag96] Here we briefly summarize aspects of the SLG WAM needed to describe scheduling strategies. In Example 2.2.1 we pointed out that in an SLG system there are several types of nodes: generator, consuming, interior and answer. Answer nodes are maintained in an explicit ....

....For simplicity of presentation, we restrict ourselves to the definite subset of the SLG WAM. It is worth pointing out, however, that we have extended Batched Scheduling to handle full negation in the current version of the SLG WAM (for more details on negation handling in the SLGWAM see [SSW96a] When a new consuming node is created under Single Stack Scheduling, CHAPTER 4. BATCHED SCHEDULING 39 the node backtracks through answers that are already in the table. To do so, a consuming choice point is placed on the choice point stack. Any new answers are later returned through answer ....

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K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Proceedings of the Joint International Conference and Symposium on Logic Programming (JICSLP), pages 274--289, 1996.

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K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 274--288, Bonn, Germany, Sept. 1996. The MIT Press.

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K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming, 2000. To Appear.

....the well founded semantics system XSB with the stable models evaluator SMODELS. Its main goal is to work as a tool for fast and interactive exploration of knowledge bases. 1 General Information The XNMR package is an attempt of integration between the well founded semantics system XSB[2, 3] and the stable models evaluator SMODELS[1] It works in UNIX platforms (e.g. Linux, Solaris) and work is being done to port it to Windows NT. The package consists of three layers. The bottom layer is a low level interface between XSB and SMODELS. This interface is written in C, and consists of ....

K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Joint International Conference and Symposium on Logic Programming., pages 274-289, 1996.

.... which are the pointers from the CHAT sub areas to the heap that need to be followed for marking and pos sible relocation: they are the trail values of the CTR sub areas, substitution factors of suspended consumers and the C[D] eld (the value of delay register as saved in each choice point; see [15]) The following things are important to note here: 1) the CHAT sub areas are allocated dynamically and in non contiguous space; how this in uences garbage collection is described in Section 4.3, and 2) in CHAT, suspended computations have parts of their execution state saved in a private area ....

....clause) in order for the answer substitution to be inserted in the table. Without proper compiler support 5 , it is quite easy for substitution factoring to become incompatible with the implementation of the garbage collector. Indeed, the compilation scheme for tabled predicates described in [14, 15] does not re ect the usefulness logic of tabled evaluations and the only alternative to changing it, is to impose strong restrictions on the order of marking. The following example illustrates the issue: 5 As a general comment, usually garbage collection requires compiler support: cf. the ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. In Proceedings of JICSLP'96, pages 274-288, Sept. 1996.

....well founded semantics is an issue orthogonal to the actual mechanism used for suspension resumption. Our current implementation of CHAT provides support for well founded negation and indeed, the handling of delaying and simplification SLG operations is similar to its handling by the SLG WAM (see [7]) We therefore mainly restrict attention to fixed order stratified negation as in [6] The SLG WAM, upon encountering a negative literal of an incomplete subgoal lays a negation suspension frame in the choice point stack and the current execution path is suspended by freezing the WAM stacks (see ....

K. Sagonas, T. Swift, and D. S. Warren. An Abstract Machine for Computing the WellFounded Semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 274--288, Bonn, Germany, Sept. 1996. The MIT Press.

....well founded semantics is an issue orthogonal to the actual mechanism used for suspension resumption. Our current implementation of CHAT provides support for well founded negation and indeed, the handling of delaying and simplification SLG operations is similar to its handling by the SLG WAM (see [7]) We therefore mainly restrict attention to xed order strati ed negation as in [6] The SLG WAM, upon encountering a negative literal of an incomplete subgoal lays a negation suspension frame in the choice point stack and the current execution path is suspended by freezing the WAM stacks (see ....

K. Sagonas, T. Swift, and D. S. Warren. An Abstract Machine for Computing the WellFounded Semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 274-288, Bonn, Germany, Sept. 1996. The MIT Press.

....sections provide a brief introduction to SLG resolution as it is implemented in XSB. For interested users, the ftp directory and web site contain papers covering in detail various aspects of tabling. An overview of SLG resolution, and a practical evaluation strategy for it are provided in [7, 28] [30, 29, 24, 15, 34, 26] describe fully the SLG WAM as it is implemented in Version 1.7.1, and [35, 6] analyze its performance. 5.1 SLG Evaluation 5.1.1 Tabling Consider the Prolog program ancestor(X,Y) parent(X,Y) ancestor(X,Y) ancestor(X,Z) parent(Z,Y) together with the query ancestor(1,Y) This ....

....Exceptions: The same as call 1 (see section 6.7) tnot( P) Tabling The semantics of tnot 1 allows for correct execution of programs with according to the wellfounded semantics. P must be a tabled predicate, For a detailed description of the actions of tabled negation for in XSB Version 1.7. 1 see [30, 29]. Chapter 5 contains further discussion of the functionality of tnot 1. Exceptions: instantiation error P is not ground (floundering occurs) type error P is not a callable term. table error P is not a call to a tabled predicate. t not ( P) Tabling Same as tnot 1 but does not check for ....

K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Joint International Conference and Symposium on Logic Programming., pages 274--289, 1996.

.... the web site contain papers covering in detail various aspects of tabling (often through the links for individuals involved in XSB) An overview of SLG resolution, and practical evaluation strategies for it are provided in [8, 41, 38, 19] The engine of XSB, the SLG WAM, is described in [35, 33, 18, 37, 7, 14] as it is implemented in Version 2.2 and its performance analyzed. Examples of large scale applications that use tabling are overviewed in [42, 9, 12] 5.1 XSB as a Prolog System Before describing how to program using tabling it is perhaps worthwhile reviewing some of the goals of XSB 1. To ....

....(see section 6.8) tnot( P) Tabling The semantics of tnot 1 allows for correct execution of programs with according to the wellfounded semantics. P must be a tabled predicate, For a detailed description of the actions of CHAPTER 6. STANDARD PREDICATES 71 tabled negation for in XSB Version 2. 2 see [35, 37]. Chapter 5 contains further discussion of the functionality of tnot 1. Exceptions: instantiation error P is not ground ( oundering occurs) type error P is not a callable term. table error P is not a call to a tabled predicate. sk not( P) Tabling Same as tnot 1 but does not check for ....

K. Sagonas, T. Swift, and D. Warren. An abstract machine for computing the well-founded semantics. In Joint International Conference and Symposium on Logic Programming., pages 274-289, 1996.

....Clear progress from Definite LPs, through Stratified and Normal LPs to Abductive LPs, Disjunctive LPs, and Quantitative LPs. Implementation and Systems [8] 129] 79] 49] 67] 98] 121] 109] 39] 9] 22] 51] 133] 99] 135] 101] 52] 42] 43] 54] 93] 107] [108], 31] XSB, YAP, Lola, and others Optimizations [36] 5 Overview ffl Magic Sets and Related Research (e.g. Alexander Method) Formulation [102] 7] 111] 124] 20] 87] 85] 10] 70] 91] 117] 47] 60] 96] 11] 114] 104] 84] References are a little dated. ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming. To appear. Preliminary version appeared in Joint International Conference and Symposium on Logic Programming, 1996, pp. 274-289, MIT Press.

....are completed, and negative literals involving these subcomponents are resolved away. If not, all subgoals in the ASCC are delayed. Second, data structures must be created to represent delayed literals in the execution stacks and tables and to support simpli cation in the tables as discussed in [10]. 3 Design Issues for a Multi Threaded Tabling Engine In keeping with Principle 1, our proposed architecture builds upon the architecture of the SLG WAM. Broadly, a new execution thread, consisting of SLG WAM stacks and registers is created when a new subgoal is queried at the top level of the ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming, 2000. To Appear.

....Call Answer , where A is an atom whose truth value depends on the truth value of some answer Answer for the subgoal Call. If is a substitution, then (A Call Answer ) A ) Call Answer . 2 Data structures for the delay elements and delay lists in the SLG WAM have been previously described [SSW96, Sag96] However these data structures were not designed to compute the correct residual program for this example, but instead compute 2 p(X,g(f(a,X) f(a,X) q(g(W) W) q(X1;Y1 ) q(g(Y1 ) Y1 ) q(g(Z) Z) undefined undefined undefined . undefined : tnot(undefined) ....

....to support correct computation of non ground residual programs. Our implementation offers the novel use of delay tries to represent delay elements and delay lists and their variable bindings. The implementation of delay tries changes many features of tabling data structures as presented in [SSW96, Sag96] which intern delay elements and delay lists, sharing them among answers. For conciseness, we refer to the representation of delay elements and delay lists presented in [SSW96, Sag96] as the delay interning approach and to the scheme presented here as the delay tries approach. In Section ....

[Article contains additional citation context not shown here]

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the wellfounded semantics. In JICSLP, pages 274--289, 1996.

.... Research Formulation [41] 17] 108] 38] 60] 98] 115] 120] 15] 14] 20] 22] 33] 19] 105] 34] 94] 54] 110] 23] 27] Implementation and Systems [6] 116] 64] 42] 2] 55] 82] 84] 106] 107] 93] 7] 21] 43] 44] 96] 121] 45] 83] [95] [92] Optimizations [30] 6 Motivation Magic Sets and Related Research (e.g. Alexander Method) Formulation [87] 5] 97] 111] 18] 69] 67] 8] 59] 73] 103] 39] 49] 79] 9] 101] 89] 66] Implementation and Systems [6] 24] 112] 80] 99] 118] 119] ....

....ffl Ordered search uses a dynamic control strategy [79] Issue: How to handle unknown undefined literals ffl One issue involves dynamically changing the computation rule ffl A second issue involves representing atoms that are neither true nor false. ffl XSB implements delay and simplification [95] ffl WFOS [101] uses the Alternating Fixpoint of [113] 81 Implementation of Tabling: Optimizations ffl Tabling is weak for acyclic right recursive queries Left: ancestor(X,Y) parent(X,Y) ancestor(X,Y) ancestor(X,Z) parent(Z,Y) Right: ancestor(X,Y) parent(X,Y) ancestor(X,Y) ....

K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Joint International Conference and Symposium on Logic Programming., 1996. 92

....original formulation of SLG; however it does not lose any of the power of SLG to formalize transfinite computations. Indeed, an informal forest of trees model of SLG has been used to derive scheduling properties of tabled evaluations [8] and to motivate the design of an abstract machine for SLG [14, 15]. Second, definitions in SLGX are geared so that underlying tabling operations are parameterizable. The first result of this paper is to prove full equivalence to SLG of SLGX parameterized with variant style operations (called in this paper SLG variance ) The second main result is to ....

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Extended version of article in Joint International Conference and Symposium on Logic Programming, 1996, pp. 274-289, MIT Press.

.... it keeps an approximation of the subgoal dependency graph (SDG) of the program in a stack (the completion stack) During the COMPLETION operation, if negative dependencies are present, the engine has to explicitly build the exact SDG of the program to detect whether negative loops are present [7, 8]. In contrast, an engine based on Local Scheduling can avoid this step: Since SCCs are preserved during the evaluation, the completion stack represents the exact SDG of the program, and thus negative dependencies are only created if there are actual loops through negation. The following example ....

....among subgoals in the completion stack. When negative dependencies are present, in order to correctly evaluate normal programs under the well founded semantics, the engine has to explicitly build the SDG of the program to determine the exact dependencies and find an independent SCC (ISCC) [8]. Given this ISCC, the engine will then check for negative loops and delay subgoals if necessary. Not only this can be a time consuming task, but also the introduction of a new data structure for the SDG increases the complexity of the actual source code. Under Local Scheduling on the other ....

K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Joint International Conference and Symposium on Logic Programming., pages 274--289, 1996.

.... which are the pointers from the CHAT sub areas to the heap that need to be followed for marking and possible relocation: they are the trail values of the CTR sub areas, substitution factors of suspended consumers and the C[D] field (the value of delay register as saved in each choice point; see [15]) Note that the C[H] field of suspended consumer choice points that reside in CHAT areas can be safely ignored by garbage collection: as mentioned this field gets a new value upon resumption of C and reinstallation of its choice point. The following things are important to note here: 1) the CHAT ....

....clause) in order for the answer substitution to be inserted in the table. Without proper compiler support 8 , it is quite easy for substitution factoring to become incompatible with the implementation of the garbage collector. Indeed, the compilation scheme for tabled predicates described in [14, 15] does not reflect the usefulness logic of tabled evaluations and the only alternative to changing it, is to impose strong restrictions on the order of marking. The following example illustrates the issue: Consider the execution of a query test. w.r.t. the tabled program given below. Here and in ....

[Article contains additional citation context not shown here]

K. Sagonas, T. Swift, and D. S. Warren. An Abstract Machine for Computing the WellFounded Semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 274--288, Bonn, Germany, Sept. 1996. The MIT Press.

No context found.

K. Sagonas, T. Swift, and D.S. Warren. An abstract machine for computing the well-founded semantics. In Proceedings of Joint International Conference and Symposium on Logic Programming, pages 274-289, Bonn, Germany, September 1996. The MIT Press.

No context found.

K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming, 2000. To Appear.

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K. Sagonas, T. Swift, and D. S. Warren. An abstract machine for computing the well-founded semantics. Journal of Logic Programming, 2000. To Appear.

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