First Order Theories for Partial Models

Staruch, Bożena

doi:10.1007/s11225-005-6779-1

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…The problems of model checking and model synthesis of partial models naturally apply in first-order logic (FOL). As mentioned earlier, a relevant study here is [22]. Here I will only add some immediate observations on this case.…”

Section: First-order Logicmentioning

confidence: 96%

“…-Conceptually closely related earlier works are: [21], proposing the use of partial structures to model multi-agent systems where the agents possess only partial information, gradually completed as the knowledge grows, and [22], taking an algebraic approach to the completion of partial first-order models, again representing partial information about the actual world. -A technique called 'partial model checking' was introduced in [2] (see also, [3], [12]) for verifying concurrent systems by gradually removing concurrent components and then reducing the specification, until completely checked, in order to avoid the state explosion problem.…”

Section: Introductionmentioning

confidence: 99%

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Model checking and model synthesisfrom partial models: a logic-based perspective

Goranko

2020

Preprint

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I consider the following generic scenario: an abstract model M of some 'real' system is only partially presented, or partially known to us, and we have to ensure that the actual system satisfies a given specification, formalised in some logical language. This scenario has at least two essentially different interpretations, leading to two, essentially different, formal logical and algorithmic problems: "Model Synthesis from Partial Models", where some 'admissible' extension of M to a full model must satisfy the specification, and "Model Checking of Partial Models", where all 'admissible' extensions of M to a full model must satisfy the specification. These problems naturally extend the classical logical decision problems of Satisfiability, Validity, and Model Checking. Here I briefly discuss both problems in the contexts of classical, modal and temporal logics. I make some observations, state some open questions, and outline a general tableaux-style procedure that solves the problem of unconstrained model synthesis from finite partial models for several well-known modal and temporal logics, incl. K, LTL, CTL, ATL.

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Section: First-order Logicmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Model checking and model synthesisfrom partial models: a logic-based perspective

Goranko

2020

Preprint

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“…an ontology, as a segmented image, whose segments are associated with a set of objects of a partial model of the ontology. To cope with the fact that a picture reports only partial information on the state of affairs we use the notion of partial model of a logical theory [30]; to cope with the possibility of having multiple alternative interpretations of a picture we introduce the notion of most plausible partial model of an image. The most plausible partial model for a picture is a partial model that maximizes a given scoring function, which depends from the low-level features of the image.…”

Section: Introductionmentioning

confidence: 99%

Mixing Low-Level and Semantic Features for Image Interpretation

Donadello

Serafini

2015

Computer Vision - ECCV 2014 Workshops

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Semantic Content-Based Image Retrieval (SCBIR) allows users to retrieve images via complex expressions of some ontological language describing a domain of interest. SCBIR adds some flexibility to the state-of-the-art methods for image retrieval, which support query either by keywords or by image examples. The price for this additional flexibility is the generation of a semantically rich description of the image content reflecting the ontology constraints. Generating these semantic interpretations is an open research problem. This paper contributes to this research line by proposing an approach for SCBIR based on the somehow natural idea that the interpretation of a picture is an (onto) logical model of an ontology that describes the domain of the picture. We implement this idea in an unsupervised method that jointly exploits the ontological constraints and the low-level features of the image. The preliminary evaluation, presented in the paper, shows promising results.

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A Topological Approximation Space Based on Open Sets of Topology Generated by Coverings

Staruch

2017

Rough Sets

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First Order Theories for Partial Models

Abstract: We investigate first order sentences valid in completions of a given partial algebraic structure -a partial model. We give semantic and syntactic description of the set of all sentences valid in every completion of the given partial model -first order theory of this model.

Cited by 3 publications

References 5 publications

Model checking and model synthesisfrom partial models: a logic-based perspective

Model checking and model synthesisfrom partial models: a logic-based perspective

Mixing Low-Level and Semantic Features for Image Interpretation

A Topological Approximation Space Based on Open Sets of Topology Generated by Coverings

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