Epistemic logic Programs (ELPs) extend Answer Set programming (ASP) with epistemic negation and have received renewed interest in recent years. This led to the development of new research and efficient solving systems...
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Epistemic logic Programs (ELPs) extend Answer Set programming (ASP) with epistemic negation and have received renewed interest in recent years. This led to the development of new research and efficient solving systems for ELPs. In practice, ELPs are often written in a modular way, where each module interacts with other modules by accepting sets of facts as input, and passing on sets of facts as output. An interesting question then presents itself: under which conditions can such a module be replaced by another one without changing the outcome, for any set of input facts? This problem is known as uniform equivalence, and has been studied extensively for ASP. For ELPs, however, such an investigation is, as of yet, missing. In this paper, we therefore propose a characterization of uniform equivalence that can be directly applied to the language of state-of-the-art ELP solvers. We also investigate the computational complexity of deciding uniform equivalence for two ELPs, and show that it is on the third level of the polynomial hierarchy.
Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. In general, a patient affected by a chronic disease can generate large amounts of event...
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Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. In general, a patient affected by a chronic disease can generate large amounts of events: for example, in Type 1 Diabetic patients generate several glucose events per day, ranging from at least 6 events per day (under normal monitoring) to 288 per day when wearing a continuous glucose monitor (CGM) that samples the blood every 5 minutes for several days. Just by itself, without considering other physiological parameters, it would be impossible for medical doctors to individually and accurately follow every patient, highlighting the need of simple approaches towards querying physiological time series. Achieving this with current technology is not an easy task, as on one hand it cannot be expected that medical doctors have the technical knowledge to query databases and on the other hand these time series include thousands of events, which requires to re-think the way data is indexed. Anyhow, handling data streams efficiently is not enough. Domain experts' knowledge must be explicitly included into PHSs in a way that it can be easily readed and modified by medical staffs. logic programming represents the perfect programming paradygm to accomplish this task. In this work, an Event Calculus-based reasoning framework to standardize and express domain-knowledge in the form of monitoring rules is suggested, and applied to three different use cases. However, if online monitoring has to be achieved, the reasoning performance must improve dramatically. For this reason, three promising mechanisms to index the Event Calculus Knowledge Base are proposed. All of them are based on different types of tree indexing structures: k-d trees, interval trees and red-black trees. The paper then compares and analyzes the performance of the three indexing techniques, by computing the time needed to check different type of rules (and eventually generating alerts), w
logic programming languages are today used to build applications accessing large database systems. This raises the possibility of building live development environments for them. Of particular interest is how specific...
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ISBN:
(纸本)9781467362641
logic programming languages are today used to build applications accessing large database systems. This raises the possibility of building live development environments for them. Of particular interest is how specific language features such as level of abstraction, transactions, etc. affect the design of such an environment. In this paper, we explore this question for a specific logic language, Datalog, contrast traditional and live approaches for its tooling and discuss issues that arise.
In this paper the authors describe their approach towards motivating students in the learning of logic programming is given. The focus here of the authors is on real world applications. Nowadays, where internet applic...
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ISBN:
(纸本)9781467352598
In this paper the authors describe their approach towards motivating students in the learning of logic programming is given. The focus here of the authors is on real world applications. Nowadays, where internet applications are still a hot topic, the development of projects related to internet applications are quite strongly motivated. Unfortunately, many of the resources used in logic programming that help us to explore the development of programs for internet purposes are not so freely available. The authors therefore had to develop much of the material used in order to be understood by first year university students, who were in fact the target group. Preliminary results showed an augmented interest in the learning of such concepts and as a result an increase in the pass rate was achieved.
This paper presents an approach to infer UI patterns existent in a web application. This reverse engineering process is performed in two steps. First, execution traces are collected from user interactions using the Se...
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ISBN:
(纸本)9781479912179
This paper presents an approach to infer UI patterns existent in a web application. This reverse engineering process is performed in two steps. First, execution traces are collected from user interactions using the Selenium software. Second, the existing UI patterns within those traces are identified using Machine Learning inference with the Aleph ILP system. The paper describes and illustrates the proposed methodology on a case study over the Amazon web site.
Relevant information extraction from text and web pages in particular is an intensive and time-consuming task that needs important semantic resources. Thus, to be efficient, automatic information extraction systems ha...
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Relevant information extraction from text and web pages in particular is an intensive and time-consuming task that needs important semantic resources. Thus, to be efficient, automatic information extraction systems have to exploit semantic resources (or ontologies) and employ machine-learning techniques to make them more adaptive. This paper presents an Ontology-based Information Extraction method using Inductive logic programming that allows inducing symbolic predicates expressed in Horn clausal logic that subsume information extraction rules. Such rules allow the system to extract class and relation instances from English corpora for ontology population purposes. Several experiments were conducted and preliminary experimental results are promising, showing that the proposed approach improves previous work over extracting instances of classes and relations, either separately or altogether.
Competence-orientation is a very important theme in engineering education. After the shifting from input to output-orientation, descriptions of learning outcomes for domains of engineering education are developed. How...
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Competence-orientation is a very important theme in engineering education. After the shifting from input to output-orientation, descriptions of learning outcomes for domains of engineering education are developed. However, descriptions of some domains are still nonexistent even though they are essential for planning lectures and for learning processes. Therefore, the author of this article developed a competence model with competence descriptions for the domain of logic programming for upper secondary education. To confirm this model, this article analyzes a test conducted in school. 25 students were tested on competences of logic programming. In particular, this article lists and analyzes these tested competences, the reached percentage and valid percentage.
Teachers' absences are a common disruption to the provision of academic courses. They make it necessary to modify teacher assignment, which amounts to finding suitable substitutions. Sometimes it happens that the ...
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In this paper we present an extension of Peirce's existential graphs to provide a diagrammatic representation of expressions in Quantified Equilibrium logic (QEL). Using this formalisation, logical connectives are...
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In this paper we present an extension of Peirce's existential graphs to provide a diagrammatic representation of expressions in Quantified Equilibrium logic (QEL). Using this formalisation, logical connectives are replaced by encircled regions (circles and squares) and quantified variables are represented as identity lines. Although the expressive power is equivalent to that of QEL, the new representation can be useful for illustrative or educational purposes.
Rule-based models are attractive for various tasks because they inherently lead to inter-pretable and explainable decisions and can easily incorporate prior knowledge. However, such systems are difficult to apply to p...
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ISBN:
(纸本)9781950737482
Rule-based models are attractive for various tasks because they inherently lead to inter-pretable and explainable decisions and can easily incorporate prior knowledge. However, such systems are difficult to apply to problems involving natural language, due to its linguistic variability. In contrast, neural models can cope very well with ambiguity by learning distributed representations of words and their composition from data, but lead to models that are difficult to interpret. In this paper, we describe a model combining neural net- works with logic programming in a novel manner for solving multi hop reasoning tasks over natural language. Specifically, we propose to use a Prolog prover which we extend to utilize a similarity function over pretrained sentence encoders. We fine-tune the representations This leads to a system that can apply rule-based reasoning to natural language, and induce domain specificrules from training data. We evaluate the proposed system on two different question answering tasks, showing that it outperforms two baselines - BIDAF (Seo et al., 2016a) and FASTQA (Weissenborn et al., 2017b) on a subset of the WIKIHOP corpus and achieves competitive results on the MEDHOP data set (Welbl et al., 2017).
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