I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 289--303. The MIT Press, 1996.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....queries. Roughly speaking this happens because Prolog and XSB do not allow reasoning by cases. This type of reasoning is incorporated in a more powerful system, called SLG [9] which was successfully used to answer queries in the presence of multiple stable models. A different type of engine, [11,17,36], are based on algorithms for computing stable models of programs without function symbols. tional specifications There are two reasons why we do that. The first advantage of the language of f specifications over A Prolog is its simplicity. The construction of f requires knowledge of a simple ....

L. Niemela and P. Simons, Efficient implementation of the well-founded and stable model semantics, in: Proc. of JICSLP-96 (MIT Press, Cambridge, MA, 1996).

....that disjunctive rule (1) can be used to express that p is exogenous as well. The possibility of expressing assumptions like (3) and (4) by disjunctive rules was essential in our experiments on the use of the system dlv [ Eiter et al. 1997 ] for planning [ Erdem, 1999 ] The system smodels [ Niemela and Simons, 1996 ] unlike dlv, accepts nondisjunctive logic programs only, and when we presented a planning problem to smodels, we had to use (2) to describe exogenous atoms. This note is organized as follows. We present the theorem in Section 2, and its proof in Section 3. After that, we compare our theorem ....

Ilkka Niemela and Patrik Simons. Efficient implementation of the well-founded and stable model semantics. In Proceedings of Joint International Cenference and Symposium on Logic Programming, pages 289--303, 1996. 7

....[Bor96, ELS97, GMN 96, DS98] Of course, the grounding approach is feasible only in restricted cases, when reasoning can be guaranteedly restricted to a finite subset of the possibly infinite set of ground instances. Even the best systems following this approach, like the S models system [NS96] quite often arrive at their limits when confronted with real data. In our application we are confronted with data sets coming from tens of thousands of units. Due to this mass, grounding of the programs before the computation starts seems not to be a viable option. Therefore, our calculus ....

Ilkka Niemela and Patrik Simons. Efficient implementation of the well-founded and stable model semantics. In Proceedings of the Joint International Conference and Symposium on Logic Programming, Bonn, Germany, 1996. The MITPress.

....that arise. Given various approaches to semantics, the problem of evaluating a logic program is quite well understood, and (beside Prolog) provers for semantics with more sophisticated treatment of negation may be used. Currently available provers include the systems DeRes [14] DLV [20] smodels [50], and XSB [52] An important aspect, however, is that an agent is situated in an environment which is subject to change. This requests the agent to adapt over time, and to adjust its decision making. An agent might be prompted to adjust its knowledge base KB after receiving new information in ....

....disjunctive logic programs (DLPs) under the answer set semantics. It allows for non ground rules and calculates answer sets by performing a reduction to the stable model semantics. Another highly efficient logic programming implementation, realizing stable model semantics, is the system smodels [50], which would be similarly apt as underlying reasoning engine. We chose DLV because of familiarity and its optimization techniques for grounding, as well as its expressiveness which would allow an integral solution to compute strict and strictly minimal answer sets, respectively. Formally, ....

I. Niemela and P. Simons. Efficient Implementation of the Well-founded and Stable Model Semantics. In M.J. Maher, editor, Proc. Thirteenth Joint International Conference and Symposium on Logic Programming, pages 289--303. MIT Press, 1996.

....queries. Roughly speaking this happens because Prolog and XSB do not allow reasoning by cases. This type of reasoning is incorporated in a more powerful system, called SLG [9] which was successfully used to answer queries in the presence of multiple stable models. A different type of engine, [36,16,35], are based on algorithms for computing stable models of programs without function symbols. 4 M. Gelfond, A. Gabaldon Building a knowledge base: an example of f , will entail exactly those facts about the new relations which belong to f(X) Programs of this sort are called lp functions. In ....

L. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics, In Proc. of JICSLP-96, MIT press, 1996.

....is the only answer set. 3 Answer Set Computation In this section, we describe the main steps of the computational process performed by ASP systems. We will describe the computational engine of the DLV system [8, 10] which will be used for the experiments, but also other ASP systems like Smodels [19, 20] employ a very similar procedure. In general, an answer set program P contains variables. The first step of a computation of an ASP system eliminates these variables, generating a ground instantiation ground(P) of P which is a (usually INFSYS RR 1843 01 07 5 much smaller) subset of all ....

Ilkka Niemela and Patrik Simons. Efficient Implementation of the Well-founded and Stable Model Semantics. In Michael J. Maher, editor, Proceedings of the 1996 Joint International Conference and Symposium on Logic Programming (ICLP'96), pages 289--303, Bonn, Germany, September 1996. MIT Press.

....that arise. Given various approaches to semantics, the problem of evaluating a logic program is quite well understood, and (beside Prolog) provers for semantics with more sophisticated treatment of negation may be used. Currently available provers include the systems DeRes [14] DLV [20] smodels [47], and XSB [49] An important aspect, however, is that an agent is situated in an environment which is subject to change. This requests the agent to adapt over time, and to adjust its decision making. An agent might be prompted to adjust its knowledge base KB after receiving new information in ....

....disjunctive logic programs (DLPs) under the answer set semantics. It allows for non ground rules and calculates answer sets by performing a reduction to the stable model semantics. Another highly efficient logic programming implementation, realizing stable model semantics, is the system smodels [47], which would be similarly apt as underlying reasoning engine. Formally, disjunctive logic programs are characterized as extended logic programs where disjunctions may appear in the head of rules; the answer set semantics for DLPs is due to Gelfond and Lifschitz [29] The implemented tasks agree ....

I. Niemela and P. Simons. Efficient Implementation of the Well-founded and Stable Model Semantics. In Proc. Joint International Conference and Symposium on Logic Programming, pages 289--303, 1996.

....is useful in many ways: 6 Using these conditions, we would be able to know if indeed the use of filtering in the papers mentioned in the previous section, results in abductive reasoning. Filtering seems to have more efficient implementations. We are aware of two systems [ELM 98,NS96] that are extremely fast at generating (stable) models of logic programs with constraints, and often use the constraints in the generation process itself to eliminate a large number of models, that would have violated constraints. These systems can be (and have been) used for filtering with ....

I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In Proc. Joint international conference and symposium on Logic programming, pages 289--303, 1996.

....authorization model. We note that, in principle, the complexity of stable model semantics is not a drawback, as it means that it is possible to express some NP complete problems. At the same time, a number of efficient techniques have recently been proposed to drastically improve its computation [24, 9, 22, 10]. For instance, the dlv system [10] which supports the stable model semantics of (disjunctive) logic programs, is able to solve hard problems, such as prime implicant 3 , very efficiently. For example, a problem instance with 202 clauses and 47 variables is 3 Prime Implicants: Find the prime ....

Niemela, I., Simons, P., Efficient Implementation of the Well-founded and Stable Model Semantics. Proc. of the 1996 Joint Int. Conf. and Symposium on Logic Programming, pp. 289--303, Bonn, Germany, 1996.

....system. In fact, the second author and his student Cheng Min Wu have implemented a propositional prioritized logic programming system (named PLPS) on 8 the digital AlphaStation. The PLPS system is based on Niemela and Simon s implementaitons of stable model semantics of logic program, i.e. smodel [5]. Details of the system implementation and performance have been reported in our another paper [7] Based on the system PLPS, we have recently implemented a rule based database update system (named RuleUpdate) which follows the update framework described in this paper. In the following, we will ....

I. Niemela and P. Simons, Efficient implementation of the well-founded and stable model semantics. In Proceedings of IJCSLP'96, pp 289-303, 1996.

....in logic programming may be easier than encoding them in classical propositional logic. 5 Computing Answer Sets To implement the planning method from [ Subrahmanian and Zaniolo, 1995 ] we need an efficient system for computing answer sets. One such system, called smodels, is described in [ Niemela and Simons, 1996 ] The current version of the system does not handle programs with classical negation, so that any answer set it computes is a set of atoms. Given, for instance, the input file p : not q. q : not p. r : p. r : q. compute all as input, smodels will generate both answer sets for program ....

Ilkka Niemela and Patrik Simons. Efficient implementation of the well-founded and stable model semantics. In Proc. Joint Int'l Conf. and Symp. on Logic Programming, pages 289--303, 1996.

....semantics with a construction based on minimal model reasoning is also very interesting, because it opens the way to apply methods from this area for efficient implementations. In particular, I. Niemela suggested very efficient methods for computing minimal models of positive disjunctive programs [31, 30, 32]. Because of our characterization, such methods can be immediately used to implement D WFS (note that we only need to consider positive disjunctive programs in Definition 6.4) Of course, there are still many open questions left for further research. An important property of our approach is its ....

Ilkka Niemela and Patrik Simons. Efficient implementation of the well-founded and stable model semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 289--303, Bonn, Germany, September 1996. The MIT Press.

....that is based on the answer set ( stable model ) approach [7] The role of logic programs under the answer set semantics as a knowledge representation language has been growing in recent years. This is evidenced by the development of software systems for computing answer sets, such as smodels [19] and dlv [5] by the emergence of stable model programming as an alternative logic programming paradigm [18] and by the use of answer sets for specifying planning problems [21,14] and for the development of efficient planning algorithms [4] The extension of the answer set semantics proposed ....

Ilkka Niemela and Patrik Simons. Efficient implementation of the well-founded and stable model semantics. In Proc. Joint Int'l Conf. and Symp. on Logic Programming, pages 289-- 303, 1996.

....shortest plan optimal in the sense of worst case complexity. We also describe an algorithm which is asymptotically optimal in the sense of average complexity. Introduction Since Kautz and Selman s paper (Kautz 1992) on satisfiability based planning there has been several work (Kautz 1996; Niemela 1996; Dimopoulos 1997; Ernst 1997; Simons 1997; Lifschitz 1999; Lifschitz 1999a; Kautz 1999) on planning through finding models of a logical theory. Most of these works focus on finding a plan of a given length. Some of the other papers that discuss finding a plan of a given length are: Wilkins 1984; ....

I. Niemela and P. Simons, "Efficient implementation of the well-founded and stable model semantics", Proceedings of Joint International Conference and Symposium on Logic Programming, 1996, pp. 289--303.

....logic programming with the stable model semantics can serve as a practical computational tool. This issue can be resolved by implementing systems computing stable models and by experimentally studying the performance of these systems. Several such projects are now under way. Niemela and Simons [16] developed a system, smodels, for computing stable models of finite function symbolfree logic programs and reported very promising performance results. For some classes of programs, smodels decides the existence of a stable model in a matter of seconds even if an input program consists of tens of ....

I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In Proceedings of JICSLP-96. MIT Press, 1996.

.... model of propositional programs is polynomial [16] while computing stable models is NP hard [12] Consequently, evaluating the well founded semantics can be used as an effective preprocessing technique in algorithms to compute stable models [15] In addition, as demonstrated by smodels [13], at present the most advanced and most efficient system to compute stable models of DATALOG : programs, the well founded semantics can be used as a powerful lookahead mechanism. Despite the importance of the well founded semantics, the question of how fast it can be computed has not attracted ....

I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In Proceedings of JICSLP-96. MIT Press, 1996.

....default reasoning [25] points out similarities and differences to default reasoning without priorities, and suggests approaches for automating prioritized default reasoning. Techniques for automating reasoning with restricted forms of prioritized defaults [2] and for defaults without priorities [19] have been presented in earlier research. A natural next step would be to extend these techniques to the more general case of prioritized default theories. ....

I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In M. Maher, editor, Proceedings of the 1996 Joint International Conference and Symposium on Logic Programming, pages 289-- 303, Bonn, Germany, September 1996. The MIT Press.

....causing any contradiction. This motivates the following definition of an operator N P;L for non monotonically inferring negative information, which is a variant of the negative component N P of Fitting operator F P . For convenience of formulation, we shall use the notion of coveredness from [78]. 6. Quasi stable Semantics 108 Definition 6.1.1 Given a logic program Pand a set L of literals. An atom p is covered by L if p is in L [ L Gamma ; otherwise it is uncovered by L. Definition 6.1.2 Given a logic program P, a set L of literals, we define two operators N P and F P on HB [ not ....

....and strong negation 2 . One significant point is that deduction is performed at compile time rather than run time. As a result, run time query execution can be reduced to the traditional relational database operations and thus can be performed relatively more efficiently than otherwise. In [78] a direct and efficient implementation of the well founded and stable model semantics has been proposed for range restricted function free logic programs. The computation of stable models for ground logic programs makes use of bottom up backtracking search and a powerful pruning method based on a ....

I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. Available from http://www.uni-koblenz.de/agki /DLP/#pubs, 1996.

....of its novel technique for approximating stable models and its over all low space complexity. 2.1. An Efficient Approach to Compute STABLE Semantics We have developed a system for computing the stable model and the well founded model semantics for rangerestricted function free normal programs [70]. It is based on new implementation techniques for general non monotonicreasoning developed in [63, 64, 69, 65] The goal has been to devise an implementation of the stable model semantics that can handle realistic size programs (tens of thousands of ground rules) with a potentially large number ....

....the minimum,maximum and average times for ten different runs on a pseudo randomly shuffled set of rules. All times are in seconds and they represent the time to find one stable model if one exists, or the time to decide that there are no stable models. For more details and further test cases, see [70]. The test results clearly show that our implementation, smodels, computes stable models significantly faster and is able to handle substantially larger examples than SLG. The key to our success appears to lie in the new approximation technique for stable models which is closely related to the ....

Ilkka Niemel a and Patrik Simons. Efficient implementation of the well-founded and stable model semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 289--303, Bonn, Germany, September 1996. The MIT Press.

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I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 289--303. The MIT Press, 1996.

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Ilkka Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. Fachbericht Informatik 7--96, Universitat Koblenz-Landau, 1996. Available at http://www.uni-koblenz.de/fb4/publikationen/gelbereihe/.

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I. Niemela and P. Simons. Efficient implementation of the well-founded and stable model semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 289--303. The MIT Press, 1996.

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I., Niemela, P., Simons. Efficient Implementation of the Well-founded and Stable Model Semantics. In Proc. of JICSLP '96, MIT Press, 1996.

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I. Niemela and P. Simons, "Efficient implementation of the well-founded and stable model semantics", Proc. Joint Int'l Conf. and Symposium on Logic Programming, 1996, pp. 289--303.

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Ilkka Niemela and Patrik Simons. Efficient Implementation of the Wellfounded and Stable Model Semantics. In M. Maher, editor, Proceedings of the Joint International Conference and Symposium on Logic Programming, pages 289--303, Bonn, Germany, September 1996. The MIT Press.

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