65 I. Niemela, P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal LP. In J. Dix, U. Furbach, A. Nerode (eds.), Logic Programming and Nonmonotonic Reasoning: 4th international conference, LPNMR'97, LNAI 1265, Springer Verlag, Berlin, 1997.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....The dependency checking combined with the ordering of inputs seems to payo in most of the cases. 5 Stable model programming A new, and growing in importance, logic programming paradigm is that of Stable Models (or Answer set) Programming [12, 13] for which several implementations already exist [14, 6]. In it, solutions to a problem are represented by the stable models [9] of the corresponding program, rather than by answer substitutions of a single model of the program, as in traditional logic programming. In traditional logic programming (as in the other approaches we present) the diagnoses ....

....For having the single faults only, the additional constraints (clauses) must be added: nonsingle : abnormal(G1) abnormal(G2) G1 = G2. nonsingle. For computing the stable models of the described program (i.e. the single fault diagnoses of the circuit) we have used the smodels system [14] version 2.26 for Windows . For dealing with the grounding of the program, required by smodels, and for preprocessing away the function symbols out 2 and in 3 used in the representation of the circuit (and not allowed by smodels) we have developed a XSB Prolog program. Though this is all that ....

I. Niemela and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In 4th LPNMR. Springer, 1997.

....to smaller components for computing its answer sets, and proving properties about the original program. To the best of our knowledge, for no other knowledge representation language has a comparable body of mathematical results been accumulated. There exist several ecient LPASS interpreters [35, 10] and LPASS has been shown to be useful in several application domains other than knowledge representation and planning. This includes policy description, product con guration, cryptography and encryption, wire routing, decision support in a space shuttle and its if then structure has been ....

....is de ned in the rst item. A program is said to be consistent if it has an answer set. Otherwise, it is inconsistent. Many robust and ecient systems that can compute answer sets of propositional logic programs have been developed. Two of the frequently used systems are dlv [10] and smodels [35]. Recently, XSB [40] a system developed for computing the well founded model of logic programs, has been extended to compute stable models of logic programs as well. 2.2.2 Problem solving using LPASS Prolog and other early logic programming systems were geared towards answering yes no queries ....

I. Niemela and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In Proceedings ICLP & LPNMR, pages 420-429, 1997.

....section we present an algorithm for calculating the topological maps associated with a set of experience E. The models associated with the causal theory (Section 4) can be calculated as the answer sets [Gelfond and Lifschitz, 1991] of a logic program. This logic program is implemented in Smodels [Niemel# a and Simons, 1997] as illustrated in [Remolina and Kuipers, 2001] It is possible to calculate the topological maps by a similar logic program. However, the number of grounding rules associated with such a program turns out to be prohibitive for practical applications. The algorithm for calculating topological ....

I. Niemel#a and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In 4th International Conference on Logic Programming and Nonmonotonic Reasoning, number 1265 in Lecture Notes in Computer Science, pages 420--429. SpringerVerlag, 1997.

....propositional satisfiability (both conjunctive normal form CNF and non CNF expressions) product configuration, AI planning, and computer aided verification problems as presented in this work, for references see e.g. 59, 61, 68] 4. 1 The Smodels System There is a tool, the Smodels system [60, 68], which provides an implementation of logic programs as a rule based constraint programming framework. It finds stable models of a logic program, and can also tell when the program has no stable models. The implementation is based on backtracking search technique similar to the Davis Putnam ....

I. Niemel and P. Simons. Smodels -- an implementation of the stable model and well-founded semantics for normal logic programs. In Proceedings of the 4th International Conference on Logic Programming and Non-Monotonic Reasoning, pages 420--429. Springer-Verlag, July 1997.

.... crucial issue, but clear specification and correctness is, Logic Programming and Non monotonic Reasoning have been brought back into the spotlight [3, 24] To this accrues the recent significant improvements in the efficiency of Logic Programming imple mentations for Non monotonic Reasoning (e.g. [22, 27, 5]) Besides allowing for a unified declarative and procedural semantics, eliminating the traditional wide gap between theory and practice, the use of several and quite powerful results in the field of non monotonic extensions to LP, such as belief revision, induc tive learning, argumentation, ....

I. Niemel':i and P. Simons. Smodels: An implementation of the stable model and well-founded semantics for normal LP. In Procs. of LPNMR'97, volume 1265 of LNAI. Springer, 1997.

....of extension in the targeted default logic. Moreover, our systems are able to do query answering in full Reiter s Default logic and this will be described in a next paper. We have to mention that, on logic programs with stable model semantics (a subcase of default logic) the system Smodels [12] has best performances. We think that it is because the bene t of our approaches has no e ect on this kind of problem whose complexity (NP complete) is less than 2 complete. But, previous people example can only be encoded in full Reiter s default logic that is beyond the scope of Smodels. ....

I. Niemel and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In Proceedings of LPNMR, volume 1265 of Lecture Notes in Articial Intelligence, pages 420429, 1997.

....ds3) ceq(dsi, ds3) ceq(dsi, ds) ViewAt(dsi, v) ViewAt(ds, v) p(x, x, p(X, Y, X2, Y1) p(X, Y, X1, Y1) ceq(X1, X2) lithe use of metrical information while building the topological map is illustrated in section 9.5.1, page 169. 12The logic program is implemented in Smodels [Niemel5 and Simons, 1997]. The output produced by Smodels is parsed in order to keep track of the different SSH causal models associated with a set of schemas. See an illustrative trace in example 34. 147 p(x, x) p(x, x, p(X,Y, X1,Y1) p(X,Y, Y1,Y2) dist(X, Y) p(X, Y, X1, Y1) viewAt(X1, V) not ....

I. Niemel/5 and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In 4th International Conference on Logic Programming and Nonmonotonic Reasoning, number 1265 in Lecture Notes in Computer Science, pages 420-429. Springer-Verlag, 1997.

....field of non monotonic extensions to Logic Programming (LP) such as belief revision, inductive learning, argumentation, preferences, abduction, etc. 15, 17] can rep resent an important added value to the design of rational agents. These results, together with the improvement in efficiency (cf. [5, 16, 18]) allow Logic Program ming and Non monotonic Reasoning to accomplish a fruitful degree of combination between reactive and rational behaviours of agents, whilst preserving clear and precise specification enjoyed by declarative languages. This goal in mind, Kowalski and Sadri [11] advanced an ....

I. Niemel' and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In Procs. of the 4th LPNMR'97, Springer, July 1997.

....4.35 establishes the maximality condition on ceq: ceq#X;Y # should be the case unless X and Y are distinguishable. In section 9.4.1 (page 147) we illustrate the use of the program for a simulated robot navigating a T like environment. We have implemented this logic program in Smodels [Niemel# # and Simons, 1997] . In the implementation, one has to add variable domain restrictions to the different rules. For example, rule ####### ## ####### # # # # becomes ####### ## ####### # # # ########## ######## # where ###### is our predicate to identify the sort of distinctive states. 33 SSH schemas summarize ....

....#### ###### # ### # # # # ######## # ### # # ######## # #### ######### # # # ############ # ############# ########### The use of metrical information while building the topological map is illustrated in section 9.5.1, page 169. The logic program is implemented in Smodels [Niemel# # and Simons, 1997] . The output produced by Smodels is parsed in order to keep track of the different SSH causal models associated with a set of schemas. See an illustrative trace in example 34. 147 ############ # ############# ##### ###### ############ # ############################# ######## ####### ##### # ....

I. Niemel#a and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In 4th International Conference on Logic Programming and Nonmonotonic Reasoning, number 1265 in Lecture Notes in Computer Science, pages 420--429. Springer-Verlag, 1997.

....to problem domain. This is afforded by the nature of its very foundation in logic, both in substance and method, and constitutes one of its major assets. To this accrues the recent significant improvements in the efficiency of Logic Programming implementations for Non monotonic Reasoning (e.g. [14, 18]) Be sides allowing for a unified dcclarativc and procedural semantics, eliminating the traditional wide gap between theory and practice, the use of several and quite powerful results in the field of non monotonic extensions to Logic Programming (LP) such as belief revision, inductive learning, ....

I. Niemel':i and P. Simons. Smodels: An implementation of the stable model and well-founded semantics for normal LP. In Procs. of LPNMR'97, volume 1265 of LNAI. Springer, 1997.

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65 I. Niemela, P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal LP. In J. Dix, U. Furbach, A. Nerode (eds.), Logic Programming and Nonmonotonic Reasoning: 4th international conference, LPNMR'97, LNAI 1265, Springer Verlag, Berlin, 1997.

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I. Niemel, P. Simons, Smodels---An implementation of the stable model and well-founded semantics for normal logic programs, in: Proc. 4th International Conference on Logic Programming and Nonmonotonic Reasoning, in: Lecture Notes in Computer Science, Vol. 1265, Springer, Berlin, 1997, pp. 420--429.

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I. Niemel and P. Simons. Smodels -- an implementation of the stable model and well-founded semantics for normal logic programs. In Proceedings of the 4th International Conference on Logic Programming and Non-Monotonic Reasoning, pages 420--429, Dagstuhl, Germany, 1997. Springer-Verlag.

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Niemel, Simons, P. (1997). Smodels -- an implementation of the stable model and well-founded semantics for normal logic programs Proc. of the 4th Int. Conf. on Logic Programming and Non-Monotonic Reasoning. Dagstuhl, Germany. http://saturn.hut.fi/pub/papers/lpnmr97-sd.ps.gz

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I. Niemel a and P. Simons. Smodels: An implementation of the stable model and well-founded semantics for normal logic programs. In Proc. LPNMR-97, pages 420--429. Springer Verlag, 1997.

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I. Niemel and P. Simons. Smodels -- an implementation of the stable model and well-founded semantics for normal logic programs. In Proceedings of the 4th International Conference on Logic Programming and Non-Monotonic Reasoning, pages 420--429, Dagstuhl, Germany, July 1997. Springer-Verlag.

No context found.

I. Niemel a and P. Simons. Smodels: An Implementation of the Stable Model and Well-Founded Semantics for Normal Logic Programs. In Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR-97), pages 420--429, 1997.

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NIEMEL I., SIMONS P., "Smodels: An implementation of the stable model and well-founded semantics for normal logic programs", DIX J., FURBACH U., NERODE A., Eds., Proceedings of the Fourth International Conference on Logic Programming and Nonmonotonic Reasoning, Springer-Verlag, 1997, p. 420-429.

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I. Niemel a and P. Simons. Smodels: An implementation of the stable model and wellfounded semantics for normal logic programs. In J. Dix, U. Furbach, and A. Nerode, editors, Proceedings of the Fourth International Conference on Logic Programing and Nonmonotonic Reasoning, pages 420--429. Springer, 1997.

No context found.

I. Niemel a and P. Simons. Smodels: An implementation of the stable model and wellfounded semantics for normal logic programs. In J. Dix, U. Furbach, and A. Nerode, editors, Proceedings of the Fourth International Conference on Logic Programming and Nonmonotonic Reasoning, pages 420--429. Springer-Verlag, 1997.

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Ilkka Niemela and P. Simons. Smodels -- an implementation of the stable model and wellfounded semantics for normal logic programs. In Proceedings of the 4th International Conference on Logic Programming and Non-Monotonic Reasoning, pages 420--429, Dagstuhl, Germany, July 1997. Springer-Verlag. I have not seen a copy of this paper. It is not online at www.springer.de.

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I. Niemel a and P. Simons, `Smodels: An implementation of the stable model and well-founded semantics for normal logic programs', in Proc. LPNMR, eds., J. Dix, U. Furbach, and A. Nerode, pp. 420--429. Springer, (1997).

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Ilkka Niemela and Patrick Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In Proc. of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 97, LNAI 1265, pages 420-429, 1997.

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Ilkka Niemela and Patrik Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In Proc. of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning, pages 420-429, 1997. Lecture Notes in Arti cial Intelligence, volume 1265.

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I. Niemel a and P. Simons. Smodels: An implementation of the stable model and well-founded semantics for normal logic programs. In J. Dix, U. Furbach, and A. Nerode, editors, Proceedings LPNMR'97, pages 420--429. Springer, 1997.

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