The Abstract interpretation is a well-established technique for performing static analyses of logic programs. However, choosing the abstract domain, widening, fixpoint, etc. that provides the best precision-cost trade...
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ISBN:
(纸本)9783030452599;9783030452605
The Abstract interpretation is a well-established technique for performing static analyses of logic programs. However, choosing the abstract domain, widening, fixpoint, etc. that provides the best precision-cost trade-off remains an open problem. This is in a good part because of the challenges involved in measuring and comparing the precision of different analyses. We propose a new approach for measuring such precision, based on defining distances in abstract domains and extending them to distances between whole analyses of a given program, thus allowing comparing precision across different analyses. We survey and extend existing proposals for distances and metrics in lattices or abstract domains, and we propose metrics for some common domains used in logic program analysis, as well as extensions of those metrics to the space of whole program analyses. We implement those metrics within the CiaoPP framework and apply them to measure the precision of different analyses on both benchmarks and a realistic program.
The last decade has witnessed remarkable improvements in the analysis of inconsistent formulas, namely in the case of Boolean Satisfiability (SAT) formulas. However, these successes have been restricted to monotonic l...
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ISBN:
(纸本)9783030518257;9783030518240
The last decade has witnessed remarkable improvements in the analysis of inconsistent formulas, namely in the case of Boolean Satisfiability (SAT) formulas. However, these successes have been restricted to monotonic logics. Recent work proposed the notion of strong inconsistency for a number of non-monotonic logics, including Answer Set programming (ASP). This paper shows how algorithms for reasoning about inconsistency in monotonic logics can be extended to the case of ASP programs, in the concrete case of strong inconsistency. Initial experimental results illustrate the potential of the proposed approach.
Justification theory is a unifying semantic framework. While it has its roots in non-monotonic logics, 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-monotonic logics, 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 logic programming.
Contemporary society is pervaded by complex processes. A company's success may depend on the proper definition, handling and management of its processes. Automated process management is fundamental to efficiently,...
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ISBN:
(纸本)9781728143842
Contemporary society is pervaded by complex processes. A company's success may depend on the proper definition, handling and management of its processes. Automated process management is fundamental to efficiently, effectively and economically carry out complex processes. In particular, process discovery is fundamental to automatically obtain process models from available executions of processes, because manually building these models is complex, costly and error-prone. Very important is incrementality in learning and adapting the models. This is not trivial, especially if the model includes multi-perspectiveness and guards. This paper describes the incremental process discovery strategy of the WOMAN framework for workflow management, based on First-Order logic. It is fully and inherently incremental, it is more expressive than standard formalisms adopted in the literature, and ensures strict adherence to the observed practices. The incremental behavior of WoMan is also analyzed, reporting several experiments that show its effectiveness and efficiency.
The amount and variety of data that we produce every day pose a constant challenge for meaningful information processing. While knowledge graphs have gained a considerable attention in the recent years, due to their f...
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ISBN:
(纸本)9789897584749
The amount and variety of data that we produce every day pose a constant challenge for meaningful information processing. While knowledge graphs have gained a considerable attention in the recent years, due to their flexible and universal knowledge representation, they lack the mechanisms facilitating knowledge processing. In this paper, we propose an information system called extended knowledge graphs (EKG) that augments the concept of knowledge graphs with procedural attachments. We put forward the requirements and assumption of the EKG structure and present a categorisation of supported reasoning tasks.
Artificial intelligence (AI) and law is an AI research area that has a history spanning more than 50 years. In the early stages, several legal-expert systems were developed. Legal-expert systems are tools designed to ...
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Artificial intelligence (AI) and law is an AI research area that has a history spanning more than 50 years. In the early stages, several legal-expert systems were developed. Legal-expert systems are tools designed to realize fair judgments in court. In addition to this research, as information and communication technologies and AI technologies have progressed, AI and law has broadened its view from legal-expert systems to legal analytics and, recently, a lot of machinelearning and text-processing techniques have been employed to analyze legal information. The research trends are the same in Japan as well and not only people involved with legal-expert systems, but also those involved with natural language processing as well as lawyers have become interested in AI and law. This report introduces the history of and the research activities on applying AI to the legal domain in Japan.
Answer-set programming (ASP) is an automated problem-solving paradigm specifically suitable for combinatorial search and optimization problems. Such problems can be solved both in theory and also increasingly in pract...
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Answer-set programming (ASP) is an automated problem-solving paradigm specifically suitable for combinatorial search and optimization problems. Such problems can be solved both in theory and also increasingly in practice by ASP technology.
The purpose of this dissertation is to contribute to ASP technology and particularly to the efficiency of ASP solving tools. In more detail, the contributions of this thesis focus on ASP optimization algorithms as well as ASP search algorithms based on so-called lazy-grounding. To these ends, several methods are proposed and shown theoretically and experimentally to have measurable performance increasing potential.
The methods belong to two novel classes of ASP transformations: optimization rewritings, aimed at enhancing optimization performance, and firstorder lazy-normalizations aimed at extending the applicability of lazy-grounding in general. On the topic of transformations, this dissertation moreover presents novel systematic ways to test and verify the correctness of certain types of ASP transformations. These verification methods are distinct in the way they compare programs, which has been designed to reflect the behavior of standard ASP solvers to be as practically relevant as possible. Regarding practical optimization performance, the value of this work is substantial as evidenced by the excellent optimization performance of the proposed techniques in the highly competitive ASP Competition series. In particular, early versions of the techniques attained first place in the optimization track of the sixth edition of the series [56]. Moreover, the included work on lazy-grounding removed an obstacle previously preventing lazy-grounding from being applied to broad classes of programs that are central to the ASP paradigm.
In planning and reasoning about action and change, reversibility of actions is the problem of deciding whether the effects of an action can be reverted by applying other actions in order to return to the original stat...
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In this article, we present a new version of the language of Epistemic Specifications. The goal is to simplify and improve the intuitive and formal semantics of the language. We describe an algorithm for computing sol...
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