According to some research, comorbidity is reported in 35 to 80% of all ill people [1]. Multiple guidelines are needed for patients with comorbid diseases. However, it is still a challenging problem to automate the ap...
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ISBN:
(数字)9783319132815
ISBN:
(纸本)9783319132815;9783319132808
According to some research, comorbidity is reported in 35 to 80% of all ill people [1]. Multiple guidelines are needed for patients with comorbid diseases. However, it is still a challenging problem to automate the application of multiple guidelines to patients because of redundancy, contraindicated, potentially discordant recommendations. In this paper, we propose a mathematical model for the problem. It formalizes and generalizes a recent approach proposed by Wilk and colleagues. We also demonstrate that our model can be encoded, in a straightforward and simple manner, in Answer Set programming ( ASP) - a class of knowledgerepresentation languages. Our preliminary experiment also shows our ASP based implementation is efficient enough to process the examples used in the literature.
We give an account of various semantics for hierarchical logic programs and discuss their properties in terms of compositionality and full abstraction when inheritance is assumed as the underlying composition mechanis...
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Vagueness is a ubiquitous feature that we know from many expressions in natural languages. It can invite a serious problem: the Sorites Paradox. The aim of this paper is to propose a new version of complete logic for ...
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ISBN:
(纸本)9783642241291;9783642241307
Vagueness is a ubiquitous feature that we know from many expressions in natural languages. It can invite a serious problem: the Sorites Paradox. The aim of this paper is to propose a new version of complete logic for vague predicates - JND-based vague predicate logic (JVL) which can avoid the Sorites Paradox and give answers to all of the Semantic Question, the Epistemological Question and the Psychological Question given by Graff. To accomplish this aim, we provide JVL with a probabilistic model by means of measurement theory.
In previous work, towards the integration of rules and ontologies in the Semantic Web, we have proposed a combination of logicprogramming under the answer set semantics with the description logics SHIF(D) and SHOIN(D...
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ISBN:
(纸本)3540238425
In previous work, towards the integration of rules and ontologies in the Semantic Web, we have proposed a combination of logicprogramming under the answer set semantics with the description logics SHIF(D) and SHOIN(D), which underly the Web ontology languages OWL Lite and OWL DL, respectively. More precisely, we have introduced description logic programs (or dl-programs), which consist of a description logicknowledge base L and a finite set of description logic rules P, and we have defined their answer set semantics. In this paper, we continue this line of research. Here, as a central contribution, we present the well-founded semantics for dl-programs, and we analyze its semantic properties. In particular, we show that it generalizes the well-founded semantics for ordinary normal programs. Furthermore, we show that in the general case, the well-founded semantics of dl-programs is a partial model that approximates the answer set semantics, whereas in the positive and the stratified case, it is a total model that coincides with the answer set semantics. Finally, we also provide complexity results for dl-programs under the well-founded semantics.
The proceedings contain 9 papers. The topics discussed include: relational artificial intelligence;logicprogramming and non-monotonic reasoning from 1991 to 2019: a personal perspective;dynamic and temporal answer se...
The proceedings contain 9 papers. The topics discussed include: relational artificial intelligence;logicprogramming and non-monotonic reasoning from 1991 to 2019: a personal perspective;dynamic and temporal answer set programming on linear finite traces;an extension of datalog for modeling and solving complex combinatorial problems;large-scale reasoning on expressive horn ontologies;constraint answer set programming without grounding and its applications;performance analysis and comparison of deductive systems and SQL databases;and feature engineering and explainability with vadalog: a recommender systems application.
作者：
Payeur, PUniv Ottawa
Sch Informat Technol & Engn Vis Imaging Video & Audio Res Lab Ottawa ON K1N 6N5 Canada
Autonomous robotic systems require a detailed model of space occupancy to be built from sensory information in order to navigate safely in their environment. Probabilistic occupancy models have been proposed that use ...
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ISBN:
(纸本)0780377834
Autonomous robotic systems require a detailed model of space occupancy to be built from sensory information in order to navigate safely in their environment. Probabilistic occupancy models have been proposed that use conditional probabilities evaluation to merge redundant measurements. These approaches provide meaningful representation of space but require important approximations to remain computationally tractable for high dimensionality, As a result, the strict definition of probability is denatured The present paper proposes an exploration of the fuzzy logic paradigm as a modeling tool for occupancy mapping in the context of work-space representation for robotic applications. A computationally tractable fuzzy logic inference engine is introduced that allows data fusion to construct a robot workspace representation in a more intuitive way while preserving desirable characteristics achieved by probabilistic modeling schemes.
This paper presents an abstract treatment of the foundations of rewriting logic, generalising in three ways: an arbitrary 2-category plays the role of the specific 2-category Cat;the foundations are rendered fully ind...
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We study a semantics for untyped, vanilla meta-programs, using the non-ground representation for object level variables. We introduce the notion of language independence for definite programs, which generalises range ...
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Existing cognitive agent programming languages that are based on the BDI model employ logical representation and reasoning for implementing the beliefs of agents. In these programming languages, the beliefs are assume...
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ISBN:
(纸本)3540331069
Existing cognitive agent programming languages that are based on the BDI model employ logical representation and reasoning for implementing the beliefs of agents. In these programming languages, the beliefs are assumed to be certain, i.e. an implemented agent can believe a proposition or not. These programming languages fail to capture the underlying uncertainty of the agent's beliefs which is essential for many real world agent applications. We introduce Dempster-Shafer theory as a convenient method to model uncertainty in agent's beliefs. We show that the computational complexity of Dempster's Rule of Combination can be controlled. In particular, the certainty value of a proposition can be deduced in linear time from the beliefs of agents, without having to calculate the combination of Dempster-Shafer mass functions.
PIE is a Prolog-embedded environment for automated reasoning on the basis of first-order logic. Its main focus is on formulas, as constituents of complex formalizations that are structured through formula macros, and ...
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