The module theorem by Janhunen et al. demonstrates how to provide a modular structure in answer set programming, where each module has a well-defined input/output interface which can be used to establish the compositi...
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The module theorem by Janhunen et al. demonstrates how to provide a modular structure in answer set programming, where each module has a well-defined input/output interface which can be used to establish the compositionality of answersets. The theorem is useful in the analysis of answerset programs, and is a basis of incremental grounding and reactive answer set programming. We extend the module theorem to the general theory of stable models by Ferraris et al. The generalization applies to non-ground logic programs allowing useful constructs in answer set programming, such as choice rules, the count aggregate, and nested expressions. Our extension is based on relating the module theorem to the symmetric splitting theorem by Ferraris et al. Based on this result, we reformulate and extend the theory of incremental answerset computation to a more general class of programs.
We propose a method to improveWeb Accessibility. First, we generate a list of Cascading Style Sheet CSS for Websites depending on user's needs and meaningful contextual information. Second, we rank this list in or...
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ISBN:
(纸本)9783642315220
We propose a method to improveWeb Accessibility. First, we generate a list of Cascading Style Sheet CSS for Websites depending on user's needs and meaningful contextual information. Second, we rank this list in order to best fit with the current user. In order to provide means for that, formally connected knowledge in user interaction processes are used to support a reasoning unit, which is based on answer set programming (ASP). Finally, visual aspects of user interfaces such as sizes of user interface elements, colours, relative position of the elements or navigation devices are specified. In Web environments, user interface adaptation is needed to tailor user interfaces to older people's needs and impairments while preserving their independence.
Many research works had been done in order to define a semantics for logic programs. Most of these semantics are iterated fixed point semantics. The main idea is the canonical model approach which is a declarative sem...
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ISBN:
(纸本)9780769549156;9781479902279
Many research works had been done in order to define a semantics for logic programs. Most of these semantics are iterated fixed point semantics. The main idea is the canonical model approach which is a declarative semantics for logic programs that can be defined by selecting for each program one of its canonical models. The notion of canonical models of a logic program is what it is called the stable models. The stable models of a logic program are the minimal Herbrand models of its "reduct" programs. The work that we describe in this paper is theoretical, we introduce a new semantics for logic programs that is different from the known fixed point semantics. In our approach, logic programs are expressed as CNF formulas (sets of clauses) of a propositional logic for which we define a notion of extension. We prove in this semantics, that each consistent CNF formula admits at least an extension and for each given stable model of a logic program there exists an extension of its corresponding CNF formula which logically entails it. On the other hand, we show that some of the extensions do not entail any stable model, in this case, we define a simple condition called a discrimination condition which allows to recognize such extensions. These extensions could be very important, but are not captured by the stable models semantics. Our approach, extends the stable model semantics in this sense. Following the new semantics, we give a full characterization of the stable models of a logic program by means of the extensions of its CNF encoding verifying the simple discrimination condition, and provide a procedure which can be used to compute such extensions from which we deduce the stable models and eventually the extrastable models of the given logic program.
In this article, we introduce fuzzy equilibrium logic as a generalization of both Pearce equilibrium logic and fuzzy answer set programming. The resulting framework combines the capability of equilibrium logic to decl...
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In this article, we introduce fuzzy equilibrium logic as a generalization of both Pearce equilibrium logic and fuzzy answer set programming. The resulting framework combines the capability of equilibrium logic to declaratively specify search problems, with the capability of fuzzy logics to model continuous domains. We show that our fuzzy equilibrium logic is a proper generalization of both Pearce equilibrium logic and fuzzy answer set programming, and we locate the computational complexity of the main reasoning tasks at the second level of the polynomial hierarchy. We then provide a reduction from the problem of finding fuzzy equilibrium logic models to the problem of solving a particular bilevel mixed integer program (biMIP), allowing us to implement reasoners by reusing existing work from the operations research community. To illustrate the usefulness of our framework from a theoretical perspective, we show that a well-known characterization of strong equivalence in Pearce equilibrium logic generalizes to our setting, yielding a practical method to verify whether two fuzzy answerset programs are strongly equivalent. Finally, to illustrate its application potential, we show how fuzzy equilibrium logic can be used to find strong Nash equilibria, even when players have a continuum of strategies at their disposal. As a second application example, we show how to find abductive explanations from Lukasiewicz logic theories.
Procedural content generation (PCG) has the potential to create unique artifacts, levels, and gameplay mechanics. However, it remains challenging to generate content that satisfies gameplay constraints: methods to ach...
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ISBN:
(纸本)9781450314473
Procedural content generation (PCG) has the potential to create unique artifacts, levels, and gameplay mechanics. However, it remains challenging to generate content that satisfies gameplay constraints: methods to achieve this include generate-and-test, search-based generation, and constructive methods. In this paper, we present a prototype, a simple game, which demonstrates the use of an off-the-shelf logic program solver, Clingo, as an easy and expressive way to model these constraint problems, and find solutions that satisfy gameplay constraints. By delegating the difficult search optimization problem to an external program, we were able to quickly prototype PCG in a low-effort way by expressing the desired content as a set of rules and constraints, keeping the focus on the designer's intentions for the generated content, rather than specific methods used to create or find it. The expressiveness and versatility of this approach is demonstrated by applying this technique to two areas of PCG in the game.
We extend the 0-approximation of sensing actions and incomplete information in Son and Baral (2001) to action theories with static causal laws and prove its soundness with respect to the possible world semantics. We a...
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We extend the 0-approximation of sensing actions and incomplete information in Son and Baral (2001) to action theories with static causal laws and prove its soundness with respect to the possible world semantics. We also show that the conditional planning problem with respect to this approximation is NP-complete. We then present an answer set programming based conditional planner, called ASCP, that is capable of generating both conformant plans and conditional plans in the presence of sensing actions, incomplete information about the initial state, and static causal laws. We prove the correctness of our implementation and argue that our planner is sound and complete with respect to the proposed approximation. Finally, we present experimental results comparing ASCP to other planners.
This technical note describes a monotone and continuous fixpoint operator to compute the answersets of programs with aggregates. The fixpoint operator relies on the notion of aggregate solution. Under certain conditi...
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This technical note describes a monotone and continuous fixpoint operator to compute the answersets of programs with aggregates. The fixpoint operator relies on the notion of aggregate solution. Under certain conditions, this operator behaves identically to the three-valued immediate consequence operator Phi(aggr)(P) for aggregate programs, independently proposed in Pelov (2004) and Pelov et al. (2004). This operator allows us to closely tie the computational complexity of the answerset checking and answersets existence problems to the cost of checking a solution of the aggregates in the program. Finally, we relate the semantics described by the operator to other proposals for logic programming with aggregates.
We have studied the update operator circle plus(1) defined for update sequences by Eiter et al. without tautologies and we have observed that it satisfies an interesting property(1). This property, which we call Weak ...
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We have studied the update operator circle plus(1) defined for update sequences by Eiter et al. without tautologies and we have observed that it satisfies an interesting property(1). This property, which we call Weak Independence of Syntax (WIS), is similar to one of the postulates proposed by Alchourron, Gardenfors, and Makinson (AGM);only that in this case it applies to nonmonotonic logic. In addition, we consider other five additional basic properties about update programs and we show that circle plus(1) satisfies them. This work continues the analysis of the AGM postulates with respect to the circle plus(1) operator under a refined view that considers N-2 as a monotonic logic which allows us to expand our understanding of answersets. Moreover, N-2 helped us to derive an alternative definition of circle plus(1) avoiding the use of unnecessary extra atoms.
We describe the reconstruction of a phylogeny for a set of taxa, with a character-based cladistics approach, in a declarative knowledge representation formalism, and show how to use computational methods of answerset...
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We describe the reconstruction of a phylogeny for a set of taxa, with a character-based cladistics approach, in a declarative knowledge representation formalism, and show how to use computational methods of answer set programming to generate conjectures about the evolution of the given taxa. We have applied this computational method in two domains: historical analysis of languages and historical analysis of parasite-host systems. In particular, using this method, we have computed some plausible phylogenies for Chinese dialects, for Indo-European language groups, and for Alcataenia species. Some of these plausible phylogenies are different from the ones computed by other software. Using this method, we can easily describe domain-specific information (e. g., temporal and geographical constraints), and thus prevent the reconstruction of some phylogenies that are not plausible.
This paper describes our methodology for building conformant planners, which is based on recent advances in the theory of action and change and answer set programming. The development of a planner for a given dynamic ...
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This paper describes our methodology for building conformant planners, which is based on recent advances in the theory of action and change and answer set programming. The development of a planner for a given dynamic domain starts with encoding the knowledge about fluents and actions of the domain as an action theory D of some action language. Our choice in this paper is AL - an action language with dynamic and static causal laws and executability conditions. An action theory D of AL defines a transition diagram T(D) containing all the possible trajectories of the domain. A transition < s, a, s'> belongs to T(D) iff the execution of the action a in the state s may move the domain to the state s'. The second step in the planner development consists in finding a deterministic transition diagram T-IP(D) such that nodes of T-IP(D) are partial states of D, its arcs are labeled by actions, and a path in T-IP(D) from an initial partial state S to a partial state satisfying the goal delta(f) corresponds to a conformant plan for delta(0) and delta(f) in T(D). The transition diagram T-IP(D) is called an 'approximation' of T(D). We claim that a concise description of an approximation of T (D) can often be given by a logic program pi(D) under the answersets semantics. Moreover, complex initial situations and constraints on plans can be also expressed by logic programming rules and included in pi(D). If this is possible then the problem of finding a parallel or sequential conformant plan can be reduced to computing answersets of pi(D). This can be done by general purpose answerset solvers. If plans are sequential and long then this method can be too time consuming. In this case, pi(D) is used as a specification for a procedural graph searching conformant planning algorithm. The paper illustrates this methodology by building several conformant planners which work for domains with complex relationship between the fluents. The efficiency of the planners is experimentally evaluat
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