Inconsistency is a natural phenomenon arising from the description of the real world. this phenomenon may be encountered in several situations. Nevertheless, human beings are capable of reasoning adequately. the autom...
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Inconsistency is a natural phenomenon arising from the description of the real world. this phenomenon may be encountered in several situations. Nevertheless, human beings are capable of reasoning adequately. the automation of such reasoning requires the development of formal theories. Paraconsistent logic was proposed by N.C.A. da Costa to provide tools to reason about inconsistencies. this paper describes an extension of the ParaLog logicprogramming Language, called ParaLoge that allows direct handling of inconsistency. Languages such as ParaLoge, capable of merging Classical logicprogramming concepts withthose of inconsistency, widen the scope of logicprogramming applications in environments presenting conflicting beliefs and contradictory information.
this paper introduces formal models for emotional reasoning, expressing emotional states and emotional causality, using action reasoning and transition systems. A general framework is defined, comprised of two main co...
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ISBN:
(纸本)9783031157073;9783031157066
this paper introduces formal models for emotional reasoning, expressing emotional states and emotional causality, using action reasoning and transition systems. A general framework is defined, comprised of two main components: 1) a model for emotions based on the Appraisal theory of Emotion (AE), and 2) a model for emotional change based on Hedonic Emotion Regulation (HER). A particular transition system is modelled in which states correspond to human emotional states and transitions correspond to restrictive (safe) ways to influence emotions while reducing negative emotional side-effects. the introduced emotional reasoning can be applied to guide a software agent's actions for dealing with emotions while estimating and planning future interactions with humans.
In the last decades, Deep Learning (DL)-based approaches have been fruitfully employed in many tasks, such as providing valuable support to computer-aided diagnosis and medicine. However, DL-based approaches are known...
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ISBN:
(纸本)9783031157073;9783031157066
In the last decades, Deep Learning (DL)-based approaches have been fruitfully employed in many tasks, such as providing valuable support to computer-aided diagnosis and medicine. However, DL-based approaches are known to suffer from some limitations;for instance, they lack of proper means for providing clear explanations and interpretations of the results, or explicitly including available knowledge to drive decisions. In this work, we present DeduDeep, the prototypical implementation of a framework explicitly conceived withthe aim of tackling such limitations by making use of deductive declarative formalisms. In particular, the framework aims at enabling the declarative encoding of explicit knowledge, and, by relying on the use of Answer Set programming (ASP), taking advantage of it for driving decisions taken by neural networks and refining the output. the framework has been tested using different artificial neural networks tailored to semantic segmentation tasks over Laryngeal Endoscopic Images and Freiburg Sitting People Images.
In recent years, Answer Set programming (ASP), logicprogramming under the stable model or answer set semantics, has seen several extensions by generalizing the notion of an atom in these programs: be it aggregate ato...
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ISBN:
(纸本)9783642405648
In recent years, Answer Set programming (ASP), logicprogramming under the stable model or answer set semantics, has seen several extensions by generalizing the notion of an atom in these programs: be it aggregate atoms, HEX atoms, generalized quantifiers, or abstract constraints, the idea is to have more complicated satisfaction patterns in the lattice of Herbrand interpretations than traditional, simple atoms. In this paper we refer to any of these constructs as generalized atoms. It is known that programs with generalized atoms that have monotonic or antimonotonic satisfaction patterns do not increase complexity with respect to programs with simple atoms (if satisfaction of the generalized atoms can be decided in polynomial time) under most semantics. It is also known that generalized atoms that are nonmonotonic (being neither monotonic nor antimonotonic) can, but need not, increase the complexity by one level in the polynomial hierarchy if non-disjunctive programs under the FLP semantics are considered. In this paper we provide the precise boundary of this complexity gap: programs with convex generalized atom never increase complexity, while allowing a single non-convex generalized atom (under reasonable conditions) always does. We also discuss several implications of this result in practice.
logic programs (LPs) and argumentation frameworks (AFs) are two declarative knowledge representation (KR) formalisms used for different reasoning tasks. the purpose of this study is interlinking two different reasonin...
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ISBN:
(纸本)9783031157073;9783031157066
logic programs (LPs) and argumentation frameworks (AFs) are two declarative knowledge representation (KR) formalisms used for different reasoning tasks. the purpose of this study is interlinking two different reasoning components. To this end, we introduce two frameworks: LPAF and AFLP. the former enables to use the result of argumentation in AF for reasoning in LP, while the latter enables to use the result of reasoning in LP for arguing in AF. these frameworks are extended to bidirectional frameworks in which AF and LP can exchange information with each other. We also investigate their connection to several general KR frameworks from the literature.
Data trees and data words have been studied extensively in connection with XML reasoning. these are trees or words that, in addition to labels from a finite alphabet, carry labels from an infinite alphabet (data). Whi...
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ISBN:
(纸本)9783642162411
Data trees and data words have been studied extensively in connection with XML reasoning. these are trees or words that, in addition to labels from a finite alphabet, carry labels from an infinite alphabet (data). While in general logics such as MSO or FO are undocidable for such extensions, decidablity results for their fragments have been obtained recently, most notably for the two-variable fragments of FO and existential MSO. the proofs, however, are very long and non-trivial, and some of them come with no complexity guarantees. Here we give a much simplified proof of the decidability of two-variable logics for data words withthe successor and data-equality predicates. In addition, the new proof provides several new fragments of lower complexity. the proof mixes database-inspired constraints with encodings in Presburger arithmetic.
In this tutorial we describe the approaches to nonmonotonicreasoning as a means for inference on the web. In particular we are focusing on the ways in which reasoning technologies have adapted to five different issu...
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ISBN:
(纸本)9783030192747;9783030192730
In this tutorial we describe the approaches to nonmonotonicreasoning as a means for inference on the web. In particular we are focusing on the ways in which reasoning technologies have adapted to five different issues of the modern era world wide web: (a) epistemic aspects, bound by the new models of the social web, (b) changes over time, (c) language variants, including different languages of deployment of a web site, (d) agent-based knowledge deployment, due to social networks and blogs, (e) dialogue aspects, introduced again in blogs and social networks. the presentation covers these aspects by a technical viewpoint, including the introduction of specific knowledge-driven methods. the technical issues will be provided within a general logical framework known as defeasible logic.
Enabling software systems to adjust their protection in continuously changing environments with imperfect context information is a grand challenging problem. the issue of uncertain reasoning based on imperfect informa...
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We give a calculus of proof-nets for classical propositional logic. these nets improve on a proposal due to Robinson by validating the associativity and commutativity of contraction, and provide canonical representant...
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ISBN:
(纸本)9783642162411
We give a calculus of proof-nets for classical propositional logic. these nets improve on a proposal due to Robinson by validating the associativity and commutativity of contraction, and provide canonical representants for classical sequent proofs modulo natural equivalences. We present the relationship between sequent proofs and proof-nets as an annotated sequent calculus, deriving formulae decorated with expansion/deletion trees. We then show a subcalculus, expansion nets, which in addition to these good properties has a polynomial-time correctness criterion.
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