Answer Set programming (ASP) is a prominent knowledge representation language with roots in logicprogramming and non-monotonicreasoning. Biennial ASP competitions are organized in order to furnish challenging benchm...
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Answer Set programming (ASP) is a prominent knowledge representation language with roots in logicprogramming and non-monotonicreasoning. Biennial ASP competitions are organized in order to furnish challenging benchmark collections and assess the advancement of the state of the art in ASP solving. In this paper, we report on the design and results of the Seventh ASP Competition, jointly organized by the University of Calabria (Italy), the University of Genova (Italy), and the University of Potsdam (Germany), in affiliation withthe 14thinternationalconference on logicprogramming and non-monotonicreasoning (LPNMR 2017).
We study the relative expressiveness of ontology-mediated queries (OMQs) formulated in the expressive Description logic ALCHOIF extended with closed predicates. In particular, we present a polynomial-time translation ...
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We currently have access to a plethora of statistical analyses based on sampling limited parts of a population. Meta-analysis is the task of combining several statistical results to obtain a more precise and reliable ...
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ISBN:
(纸本)9780999241172
We currently have access to a plethora of statistical analyses based on sampling limited parts of a population. Meta-analysis is the task of combining several statistical results to obtain a more precise and reliable picture of the population. By the nature of sampling, all these results are uncertain, and difficult to combine with other knowledge. In this position paper, we propose a first approach for automated reasoning in meta-analyses.
In a recent paper Lakemeyer and Levesque proposed a first-order logic of limited belief to characterize the beliefs of a knowledge base (KB). Among other things, they show that their model of belief is expressive, eve...
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ISBN:
(纸本)9780999241172
In a recent paper Lakemeyer and Levesque proposed a first-order logic of limited belief to characterize the beliefs of a knowledge base (KB). Among other things, they show that their model of belief is expressive, eventually complete, and tractable. this means, roughly, that a KB may consist of arbitrary first-order sentences, that any sentence which is logically entailed by the KB is eventually believed, given enough reasoning effort, and that reasoning is tractable under reasonable assumptions. One downside of the proposal is that epistemic states are defined in terms of sets of clauses, possibly containing variables, giving the logic a distinct syntactic flavour compared to the more traditional possible-world semantics found in the literature on epistemic logic. In this paper we show that the same properties as above can be obtained by defining epistemic states as sets of three-valued possible worlds. this way we are able to shed new light on those properties by recasting them using the more familiar notion of truth over possible worlds.
Justification theory is a unifying semantic framework. While it has its roots in non-monotoniclogics, it can be applied to various areas in computer science, especially in explainable reasoning;its most central conce...
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Justification theory is a unifying semantic framework. While it has its roots in non-monotoniclogics, it can be applied to various areas in computer science, especially in explainable reasoning;its most central concept is a justification: an explanation why a property holds (or does not hold) in a model. In this paper, we continue the study of justification theory by means of three major contributions. the first is studying the relation between justification theory and game theory. We show that justification frameworks can be seen as a special type of games. the established connection provides the theoretical foundations for our next two contributions. the second contribution is studying under which condition two different dialects of justification theory (graphs as explanations vs trees as explanations) coincide. the third contribution is establishing a precise criterion of when a semantics induced by justification theory yields consistent results. In the past proving that such semantics were consistent took cumbersome and elaborate proofs. We show that these criteria are indeed satisfied for all common semantics of logicprogramming.
Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. logic-based approaches are of special interest in CER, since, via Statistical Relationa...
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ISBN:
(纸本)9780999241172
Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We presentWOLED, a system based on Answer Set programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt online. We compare our ASP-based implementation with a Markov logic-based one and with a crisp version of the algorithm that learns unweighted rules, on CER datasets for activity recognition, maritime surveillance and fleet management. Our results demonstrate the superiority of our novel implementation, both in terms of efficiency and predictive performance.
the logic of information flows (LIF) is a general framework in which tasks of a procedural nature can be modeled in a declarative, logic-based fashion. the first contribution of this paper is to propose semantic and s...
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ISBN:
(纸本)9780999241172
the logic of information flows (LIF) is a general framework in which tasks of a procedural nature can be modeled in a declarative, logic-based fashion. the first contribution of this paper is to propose semantic and syntactic definitions of inputs and outputs of LIF expressions. We study how the two relate and show that our syntactic definition is optimal in a sense that is made precise. the second contribution is a systematic study of the expressive power of sequential composition in LIF. Our results on composition tie in the results on inputs and outputs, and relate LIF to first-order logic (FO) and bounded-variable LIF to bounded-variable FO.
nondeterministic strategies are strategies (or protocols, or plans) that, given a history in a game, assign a set of possible actions, all of which should be winning. An important problem is that of refining such stra...
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ISBN:
(纸本)9780999241172
nondeterministic strategies are strategies (or protocols, or plans) that, given a history in a game, assign a set of possible actions, all of which should be winning. An important problem is that of refining such strategies. For instance, given a nondeterministic strategy that allows only safe executions, refine it to, additionally, eventually reach a desired state of affairs. We show that strategic problems involving strategy refinement can be solved elegantly in the framework of Strategy logic (SL), a very expressive logic to reason about strategic abilities. Specifically, we introduce an extension of SL withnondeterministic strategies and an operator expressing strategy refinement. We show that model checking this logic can be done at no additional computational cost with respect to standard SL, and can be used to solve a variety of problems such as synthesis of maximally permissive strategies or maximally permissive Nash equilibria.
the proceedings contain 94 papers. the topics discussed include: inputs, outputs, and composition in the logic of information flows;reasoning with contextual knowledge and influence diagrams;verifying strategic abilit...
ISBN:
(纸本)9781713825982
the proceedings contain 94 papers. the topics discussed include: inputs, outputs, and composition in the logic of information flows;reasoning with contextual knowledge and influence diagrams;verifying strategic abilities of neural-symbolic multi-agent systems;explainable acceptance in probabilistic abstract argumentation: complexity and approximation;answer set programming with composed predicate names;symbolic solutions for symbolic constraint satisfaction problems;an answer set programming framework for reasoning about agents' beliefs and truthfulness of statements;syntax splitting for iterated contractions;reasoning with inconsistent knowledge using the epistemic approach to probabilistic argumentation;plausible reasoning about el-ontologies using concept interpolation;and on the decidability of expressive description logics with transitive closure and regular role expressions.
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