This paper presents the concept of parallelisation of a solver for answer set programming (ASP). While there already exist some approaches to parallel ASP solving, there was a lack of a parallel version of the powerfu...
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ISBN:
(纸本)9783642037696
This paper presents the concept of parallelisation of a solver for answer set programming (ASP). While there already exist some approaches to parallel ASP solving, there was a lack of a parallel version of the powerful clasp solver. We implemented a parallel version of clasp based on message-passing. Experimental results on Blue Gene P/L indicate the potential of such an approach.
Following the argumentation framework and semantics proposed by Dung, we are interested in the problem of deciding which set of acceptable arguments support the decision making in an agent-based platform called CARREL...
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ISBN:
(纸本)0769524540
Following the argumentation framework and semantics proposed by Dung, we are interested in the problem of deciding which set of acceptable arguments support the decision making in an agent-based platform called CARREL. It is an agent-agency which mediates organ transplants. We present two possible ways to infer the stable and preferred extensions of an argumentation framework, one in a declarative way using answer set programming(ASP) and the other one in a procedure way.
This paper deals with four solvers for combinatorial problems: the commercial state-of-the-art solver ILOG OPLSTUDIO, and the research answer set programming (ASP) systems DLV, SMODELS and CMODELS. The first goal of t...
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This paper deals with four solvers for combinatorial problems: the commercial state-of-the-art solver ILOG OPLSTUDIO, and the research answer set programming (ASP) systems DLV, SMODELS and CMODELS. The first goal of this research is to evaluate the relative performance of such systems when used in a purely declarative way, using a reproducible and extensible experimental methodology. In particular, we consider a third-party problem library, i.e., the CSPLib, and uniform rules for modelling and instance selection. The second goal is to analyze the marginal effects of popular reformulation techniques on the various solving technologies. In particular, we consider structural symmetry breaking, the adoption of global constraints, and the addition of auxiliary predicates. Finally, we evaluate, on a subset of the problems, the impact of numbers and arithmetic constraints on the different solving technologies. Results show that there is not a single solver winning on all problems, and that reformulation is almost always beneficial: symmetry-breaking may be a good choice, but its complexity has to be carefully chosen, by taking into account also the particular solver used. Global constraints often, but not always, help OPL, and the addition of auxiliary predicates is usually worth, especially when dealing with ASP solvers. Moreover, interesting synergies among the various modelling techniques exist.
The notion of maintenance often appears in the AI literature in the context of agent behavior and planning. In this paper, we argue that earlier characterizations of the notion of maintenance are not intuitive to char...
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The notion of maintenance often appears in the AI literature in the context of agent behavior and planning. In this paper, we argue that earlier characterizations of the notion of maintenance are not intuitive to characterize the maintenance behavior of certain agents in a dynamic environment. We propose a different characterization of maintenance and distinguish it from earlier notions such as stabilizability. Our notion of maintenance is more sensitive to a good-natured agent which struggles with an "adversary" environment, which hinders her by unforeseeable events to reach her goals (not in principle, but in case). It has a parameter k, referring to the length of non-interference (from exogenous events) needed to maintain a goal;we refer to this notion as k-maintainability. We demonstrate the notion on examples, and address the important but non-trivial issue of efficient construction of maintainability control functions. We present an algorithm which in polynomial time constructs a k-maintainable control function, if one exists, or tells that no such control is possible. Our algorithm is based on SAT Solving, and employs a suitable formulation of the existence of k-maintainable control in a fragment of SAT which is tractable. For small k (bounded by a constant), our algorithm is linear time. We then give a logic programming implementation of our algorithm and use it to give a standard procedural algorithm, and analyze the complexity of constructing k-maintainable controls, under different assumptions such as k = 1, and states described by variables. On the one hand, our work provides new concepts and algorithms for maintenance in dynamic environment, and on the other hand, a very fruitful application of computational logic tools. We compare our work with earlier works on control synthesis from temporal logic specification and relate our work to Dijkstra's notion of self-stabilization and related notions in distributed computing. (c) 2008 Elsevier B.V. All rights
In the last few years, microprocessor technologies have been moving towards multi-core architectures, in order to improve performance as well as reduce power consumption. This makes real Symmetric MultiProcessing (SMP...
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In the last few years, microprocessor technologies have been moving towards multi-core architectures, in order to improve performance as well as reduce power consumption. This makes real Symmetric MultiProcessing (SMP) available even on nondedicated machines, and paves the way to the development of better performing software. Notably, the recent application of answer set programming (ASP) in different emerging areas, such as knowledge management or information extraction/integration, shows that performance is a crucial issue also for ASP systems. Among the tasks performed by such systems, the instantiation process, which consists of generating a variable-free program equivalent to the input one, is one of the most expensive from a computational viewpoint, especially in the case of huge input data. In this paper a new strategy exploiting parallelism for the instantiation of ASP programs is proposed. An implementation of this strategy and its integration with the grounding module of the DLV system is discussed. The results of an experimental analysis are also presented, which confirm that the strategy is effective in making ASP instantiation more efficient. (c) 2008 Elsevier Inc. All fights reserved.
Disjunctive logic programming (DLP) is a very expressive formalism. It allows for expressing every property of finite structures that is decidable in the complexity class Sigma(P)(2) (=NPNP). Despite this high express...
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Disjunctive logic programming (DLP) is a very expressive formalism. It allows for expressing every property of finite structures that is decidable in the complexity class Sigma(P)(2) (=NPNP). Despite this high expressiveness, there are some simple properties, often arising in real-world applications, which cannot be encoded in a simple and natural manner. Especially properties that require the use of arithmetic operators (like sum, times, or count) on a set or multiset of elements, which satisfy some conditions, cannot be naturally expressed in classic DLP. To overcome this deficiency, we extend DLP by aggregate functions in a conservative way. In particular, we avoid the introduction of constructs with disputed semantics, by requiring aggregates to be stratified. We formally define the semantics of the extended language (called DLPA), and illustrate how it can be profitably used for representing knowledge. Furthermore, we analyze the computational complexity of DLPA, showing that the addition of aggregates does not bring a higher cost in that respect. Finally, we provide an implementation of DLPA in DLV-a state-of-the-art DLP system-and report on experiments which confirm the usefulness of the proposed extension also for the efficiency of computation.
In this paper, a Gaifman-Shapiro-style module architecture is tailored to the case of SMODELS programs under the stable model semantics. The composition of SMODELS program modules is suitably limited by module conditi...
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In this paper, a Gaifman-Shapiro-style module architecture is tailored to the case of SMODELS programs under the stable model semantics. The composition of SMODELS program modules is suitably limited by module conditions which ensure the compatibility of the module system with stable models. Hence the semantics of an entire SMODELS program depends directly on stable models assigned to its modules. This result is formalized as a module theorem which truly strengthens V. Lifschitz and H. Turner's splitting-set theorem (June 1994, Splitting a logic program. In Logic programming: Proceedings of the Eleventh International Conference on Logic programming, Santa Margherita Ligure, Italy, P. V. Hentenryck, Ed. MIT Press, 23-37) for the class of SMODELS programs. To streamline generalizations in the future, the module theorem is first proved for normal programs and then extended to cover SMODELS programs using a translation from the latter class of programs to the former class. Moreover, the respective notion of module-level equivalence, namely modular equivalence, is shown to be a proper congruence relation: it is preserved under substitutions of modules that are modularly equivalent. Principles for program decomposition are also addressed. The strongly connected components of the respective dependency graph can be exploited in order to extract it module structure when there is no explicit a priori knowledge about the modules of a program. The paper includes a practical demonstration of tools that have been developed for automated (de)composition of SMODELS programs.
The paper presents a new modality extending answer set programming in order to refine its capability of representing knowledge in case of possible perception failure. The aim of the proposal is mainly to present a new...
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The paper presents a new modality extending answer set programming in order to refine its capability of representing knowledge in case of possible perception failure. The aim of the proposal is mainly to present a new logical approach to deal with uncertainty arising from perception bugs, and to show its effectiveness in the context of agent reasoning representation.
In this paper, we study the relation among answer set programming (ASP) systems from a computational point of view. We consider SMODELS, DLV, and CMODELS ASP systems based on stable model semantics, the first two bein...
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In this paper, we study the relation among answer set programming (ASP) systems from a computational point of view. We consider SMODELS, DLV, and CMODELS ASP systems based on stable model semantics, the first two being native ASP systems and the last being a SAT-based system. We first show that SMODELS, DLV, and CMODELS explore search trees with the same branching nodes (assuming, of course, a same branching heuristic) on the class of tight logic programs. Leveraging on the fact that SAT-based systems rely on the deeply studied Davis-Logemann-Loveland (DLL) algorithm, we derive new complexity results for the ASP procedures. We also show that on nontight programs the SAT-based systems are computationally different from native procedures, and the latter have computational advantages. Moreover, we show that native procedures can guarantee the "correctness" of a reported solution when reaching the leaves of the search trees (i.e., no stability check is needed), while this is not the case for SAT-based procedures on nontight programs. A similar advantage holds for DLV in comparison with SMODELS if the "well-founded" operator is disabled and only Fitting's operator is used for negative inferences. We finally study the "cost" of achieving such advantages and comment on to what extent the results presented extend to other systems.
We introduce an extended tableau calculus for answer set programming (ASP). The proof system is based on the ASP tableaux defined in the work by Gebser and Schaub (Tableau calculi for answer set programming. In Procee...
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We introduce an extended tableau calculus for answer set programming (ASP). The proof system is based on the ASP tableaux defined in the work by Gebser and Schaub (Tableau calculi for answer set programming. In Proceedings of the 22nd International Conference on Logic programming (ICLP 2006), S. Etalle and M. Truszczynski, Eds. Lecture Notes in Computer Science, vol. 4079. Springer, 11-25) with an added extension rule. We investigate the power of Extended ASP Tableaux both theoretically and empirically. We study the relationship of Extended ASP Tableaux with the Extended Resolution proof system defined by Tseitin for sets of clauses, and separate Extended ASP Tableaux from ASP Tableaux by giving a polynomial-length proof for a family of normal logic programs {Pi(n)} for which ASP Tableaux has exponential-length minimal proofs with respect to n. Additionally, Extended ASP Tableaux imply interesting insight into the effect of program simplification on the lengths of proofs in ASP. Closely related to Extended ASP Tableaux, we empirically investigate the effect of redundant rules on the efficiency of ASP solving.
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