Theory and Practice of Logic Programming最新文献

英文中文

sm ProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation sm ProbLog: ProbLog中用于概率论证的稳定模型语义

2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-05-25 DOI: 10.1017/s147106842300008x

PIETRO TOTIS, LUC DE RAEDT, ANGELIKA KIMMIG

Abstract Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabilistic argumentation frameworks provide modeling tools to account for it. The first contribution of this paper is a novel interpretation of probabilistic argumentation frameworks as probabilistic logic programs. Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. We show that the programs representing probabilistic argumentation frameworks do not satisfy a common assumption in probabilistic logic programming (PLP) semantics, which is, that probabilistic facts fully capture the uncertainty in the domain under investigation. The second contribution of this paper is then a novel PLP semantics for programs where a choice of probabilistic facts does not uniquely determine the truth assignment of the logical atoms. The third contribution of this paper is the implementation of a PLP system supporting this semantics: sm ProbLog. sm ProbLog is a novel PLP framework based on the PLP language ProbLog. sm ProbLog supports many inference and learning tasks typical of PLP, which, together with our first contribution, provide novel reasoning tools for probabilistic argumentation. We evaluate our approach with experiments analyzing the computational cost of the proposed algorithms and their application to a dataset of argumentation problems.

摘要论证问题涉及从一组论证的关系结构中确定它们的可接受性。当可用信息不确定时，概率论证框架提供建模工具来解释它。本文的第一个贡献是将概率论证框架解释为概率逻辑程序。概率逻辑程序是用概率标注某些事实的逻辑程序。我们表明，表示概率论证框架的程序不满足概率逻辑规划(PLP)语义中的一个常见假设，即概率事实完全捕获了所研究领域的不确定性。本文的第二个贡献是一个新颖的PLP语义，其中概率事实的选择并不唯一地决定逻辑原子的真值分配。本文的第三个贡献是实现了一个支持这种语义的PLP系统:sm ProbLog。sm ProbLog是一种基于PLP语言ProbLog的新型PLP框架。sm ProbLog支持PLP的许多推理和学习任务，这与我们的第一个贡献一起，为概率论证提供了新的推理工具。我们通过实验来评估我们的方法，分析所提出算法的计算成本及其在论证问题数据集上的应用。

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引用次数: 2

Distributed Subweb Specifications for Traversing the Web 用于遍历Web的分布式子Web规范

2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-04-25 DOI: 10.1017/s1471068423000054

BART BOGAERTS, BAS KETSMAN, YOUNES ZEBOUDJ, HEBA AAMER, RUBEN TAELMAN, RUBEN VERBORGH

Abstract Link traversal–based query processing ( ltqp ), in which a sparql query is evaluated over a web of documents rather than a single dataset, is often seen as a theoretically interesting yet impractical technique. However, in a time where the hypercentralization of data has increasingly come under scrutiny, a decentralized Web of Data with a simple document-based interface is appealing, as it enables data publishers to control their data and access rights. While ( ltqp allows evaluating complex queries over such webs, it suffers from performance issues (due to the high number of documents containing data) as well as information quality concerns (due to the many sources providing such documents). In existing ltqp approaches, the burden of finding sources to query is entirely in the hands of the data consumer . In this paper, we argue that to solve these issues, data publishers should also be able to suggest sources of interest and guide the data consumer toward relevant and trustworthy data. We introduce a theoretical framework that enables such guided link traversal and study its properties. We illustrate with a theoretic example that this can improve query results and reduce the number of network requests. We evaluate our proposal experimentally on a virtual linked web with specifications and indeed observe that not just the data quality but also the efficiency of querying improves.

基于链接遍历的查询处理(ltqp)，其中sparql查询在文档网络而不是单个数据集上进行评估，通常被视为理论上有趣但不切实际的技术。然而，在数据的高度集中化日益受到严格审查的时代，具有简单的基于文档的界面的分散的数据Web很有吸引力，因为它使数据发布者能够控制他们的数据和访问权限。虽然ltqp允许评估此类web上的复杂查询，但它存在性能问题(由于包含数据的文档数量很多)和信息质量问题(由于提供此类文档的来源很多)。在现有的ltqp方法中，查找要查询的数据源的负担完全由数据使用者承担。在本文中，我们认为，为了解决这些问题，数据发布者还应该能够建议感兴趣的来源，并引导数据消费者获得相关和可信的数据。我们介绍了一个理论框架，使这种引导链接遍历和研究其性质。通过一个理论实例说明，这样可以改善查询结果，减少网络请求的数量。我们在一个有规范的虚拟链接网络上对我们的建议进行了实验评估，并确实观察到不仅数据质量而且查询效率都有所提高。

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引用次数: 0

Introduction to the Special Issue on Logic Rules and Reasoning: Selected Papers from the 4th International Joint Conference on Rules and Reasoning (RuleML+RR 2020) 逻辑规则与推理特刊简介：第四届规则与推理国际联席会议论文选集（RuleML+RR2020）

IF 1.4 2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-04-24 DOI: 10.1017/s1471068423000042

Tomáš Kliegr, Víctor Gutiérrez-Basulto, A. Soylu

引用次数: 0

Extended High-Utility Pattern Mining: An Answer Set Programming-Based Framework and Applications 扩展的高效用模式挖掘:基于答案集编程的框架与应用

2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-04-19 DOI: 10.1017/s1471068423000066

FRANCESCO CAUTERUCCIO, GIORGIO TERRACINA

Abstract Detecting sets of relevant patterns from a given dataset is an important challenge in data mining. The relevance of a pattern, also called utility in the literature, is a subjective measure and can be actually assessed from very different points of view. Rule-based languages like Answer Set Programming (ASP) seem well suited for specifying user-provided criteria to assess pattern utility in a form of constraints; moreover, declarativity of ASP allows for a very easy switch between several criteria in order to analyze the dataset from different points of view. In this paper, we make steps toward extending the notion of High-Utility Pattern Mining; in particular, we introduce a new framework that allows for new classes of utility criteria not considered in the previous literature. We also show how recent extensions of ASP with external functions can support a fast and effective encoding and testing of the new framework. To demonstrate the potential of the proposed framework, we exploit it as a building block for the definition of an innovative method for predicting ICU admission for COVID-19 patients. Finally, an extensive experimental activity demonstrates both from a quantitative and a qualitative point of view the effectiveness of the proposed approach.

从给定数据集中检测出相关模式集是数据挖掘中的一个重要挑战。模式的相关性，在文献中也称为效用，是一种主观度量，实际上可以从非常不同的角度进行评估。基于规则的语言，如答案集编程(ASP)，似乎非常适合指定用户提供的标准，以约束的形式评估模式的效用;此外，ASP的声明性允许在几个标准之间非常容易地切换，以便从不同的角度分析数据集。在本文中，我们为扩展高效用模式挖掘的概念迈出了一步;特别是，我们引入了一个新的框架，允许以前文献中没有考虑到的新类别的效用标准。我们还展示了最近的带有外部函数的ASP扩展如何支持对新框架进行快速有效的编码和测试。为了证明所提出的框架的潜力，我们将其作为构建块，用于定义预测COVID-19患者ICU入院的创新方法。最后，广泛的实验活动从定量和定性的角度证明了所提出方法的有效性。

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引用次数: 4

Solving Rehabilitation Scheduling Problems via a Two-Phase ASP Approach 用两阶段ASP方法解决康复计划问题

2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-04-17 DOI: 10.1017/s1471068423000030

MATTEO CARDELLINI, PAOLO DE NARDI, CARMINE DODARO, GIUSEPPE GALATÀ, ANNA GIARDINI, MARCO MARATEA, IVAN PORRO

Abstract A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical, and ethical requirements and optimizations, for example, patient’s preferences and operator’s work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation’s needs. In this paper, we present a two-phase solution to rehabilitation scheduling based on Answer Set Programming, which proved to be an effective tool for solving practical scheduling problems. We first present a general encoding and then add domain-specific optimizations. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution as well as the impact of our domain-specific optimizations.

康复调度过程的核心部分是通过考虑患者的偏好和操作员的工作平衡等法律、医疗和伦理方面的要求和优化，在给定的一天的特定时间段为患者分配合适的操作员，为患者规划康复物理治疗课程。能够有效地解决这一问题至关重要，特别是在COVID-19大流行之后，康复需求大幅增加。本文提出了一种基于答案集规划的康复调度的两阶段求解方法，该方法被证明是解决实际调度问题的有效工具。我们首先给出一个通用编码，然后添加特定于领域的优化。在合成基准和真实基准(后者由ICS Maugeri提供)上执行的实验结果显示了我们的解决方案的有效性以及我们特定领域优化的影响。

引用次数: 0

Disjunctive Delimited Control 析取分隔控制

2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-04-11 DOI: 10.1017/s1471068423000029

ALEXANDER VANDENBROUCKE, TOM SCHRIJVERS

Abstract Delimited control is a powerful mechanism for programming language extension which has been recently proposed for Prolog (and implemented in SWI-Prolog). By manipulating the control flow of a program from inside the language, it enables the implementation of powerful features, such as tabling, without modifying the internals of the Prolog engine. However, its current formulation is inadequate: it does not capture Prolog’s unique non-deterministic nature which allows multiple ways to satisfy a goal. This paper fully embraces Prolog’s non-determinism with a novel interface for disjunctive delimited control, which gives the programmer not only control over the sequential (conjunctive) control flow, but also over the non-deterministic control flow. We provide a meta-interpreter that conservatively extends Prolog with delimited control and show that it enables a range of typical Prolog features and extensions, now at the library level: findall, cut, branch-and-bound optimisation, probabilistic programming, …

分隔控制是一种强大的编程语言扩展机制，它最近被提出用于Prolog(并在SWI-Prolog中实现)。通过在语言内部操纵程序的控制流，它可以实现强大的功能，例如表，而无需修改Prolog引擎的内部。然而，它目前的表述是不充分的:它没有捕捉到Prolog独特的非确定性性质，允许多种方法来满足一个目标。本文充分利用Prolog的非确定性，为析取定界控制提供了一个新的接口，使程序员不仅可以控制顺序(合取)控制流，还可以控制非确定性控制流。我们提供了一个元解释器，它保守地扩展了带有分隔控制的Prolog，并显示它支持一系列典型的Prolog功能和扩展，现在在库级别:findall, cut，分支和绑定优化，概率编程，…

引用次数: 0

Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling 并行机器调度中词典最大完工时间优化的答案集规划

2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2023-01-26 DOI: 10.1017/s1471068423000017

THOMAS EITER, TOBIAS GEIBINGER, NYSRET MUSLIU, JOHANNES OETSCH, PETER SKOČOVSKÝ, DARIA STEPANOVA

Abstract We deal with a challenging scheduling problem on parallel machines with sequence-dependent setup times and release dates from a real-world application of semiconductor work-shop production. There, jobs can only be processed by dedicated machines, thus few machines can determine the makespan almost regardless of how jobs are scheduled on the remaining ones. This causes problems when machines fail and jobs need to be rescheduled. Instead of optimising only the makespan, we put the individual machine spans in non-ascending order and lexicographically minimise the resulting tuples. This achieves that all machines complete as early as possible and increases the robustness of the schedule. We study the application of answer-set programming (ASP) to solve this problem. While ASP eases modelling, the combination of timing constraints and the considered objective function challenges current solving technology. The former issue is addressed by using an extension of ASP by difference logic. For the latter, we devise different algorithms that use multi-shot solving. To tackle industrial-sized instances, we study different approximations and heuristics. Our experimental results show that ASP is indeed a promising knowledge representation and reasoning (KRR) paradigm for this problem and is competitive with state-of-the-art constraint programming (CP) and Mixed-Integer Programming (MIP) solvers.

摘要:本文从半导体车间生产的实际应用中，处理具有顺序相关的安装时间和发布日期的并行机器上具有挑战性的调度问题。在这种情况下，作业只能由专用的机器来处理，因此很少有机器可以确定完工时间，而不管剩余机器上的作业是如何调度的。当机器发生故障并且需要重新调度作业时，这会导致问题。我们不是只优化makespan，而是将各个机器跨度按非升序排列，并按字典顺序最小化结果元组。这实现了所有机器尽可能早地完成，并增加了调度的健壮性。为了解决这一问题，我们研究了答案集规划(ASP)的应用。虽然ASP简化了建模，但时间约束和考虑的目标函数的组合对当前的求解技术提出了挑战。前一个问题是通过使用基于差异逻辑的ASP扩展来解决的。对于后者，我们设计了使用多镜头求解的不同算法。为了处理工业规模的实例，我们研究了不同的近似和启发式方法。我们的实验结果表明，ASP确实是解决该问题的一种有前途的知识表示和推理(KRR)范式，并且与最先进的约束规划(CP)和混合整数规划(MIP)求解器竞争。

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引用次数: 0

Unifying Framework for Optimizations in Non-Boolean Formalisms 非布尔形式优化的统一框架

IF 1.4 2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2022-11-15 DOI: 10.1017/s1471068422000400

YULIYA LIERLER

Search-optimization problems are plentiful in scientific and engineering domains. Artificial intelligence (AI) has long contributed to the development of search algorithms and declarative programming languages geared toward solving and modeling search-optimization problems. Automated reasoning and knowledge representation are the subfields of AI that are particularly vested in these developments. Many popular automated reasoning paradigms provide users with languages supporting optimization statements. Recall integer linear programming, MaxSAT, optimization satisfiability modulo theory, (constraint) answer set programming. These paradigms vary significantly in their languages in ways they express quality conditions on computed solutions. Here we propose a unifying framework of so-called extended weight systems that eliminates syntactic distinctions between paradigms. They allow us to see essential similarities and differences between optimization statements provided by distinct automated reasoning languages. We also study formal properties of the proposed systems that immediately translate into formal properties of paradigms that can be captured within our framework.

搜索优化问题在科学和工程领域中比比皆是。人工智能(AI)长期以来为搜索算法和声明性编程语言的发展做出了贡献，这些语言旨在解决和建模搜索优化问题。自动推理和知识表示是人工智能的子领域，特别是在这些发展中。许多流行的自动推理范例为用户提供了支持优化语句的语言。召回整数线性规划，MaxSAT，优化可满足模理论，(约束)答案集规划。这些范例在表达计算解的质量条件的方式上有很大的语言差异。在这里，我们提出了一个所谓的扩展权重系统的统一框架，它消除了范式之间的语法差异。它们使我们能够看到由不同的自动推理语言提供的优化语句之间的本质相似性和差异性。我们还研究了被提议的系统的形式属性，这些系统可以立即转化为范式的形式属性，这些范式可以在我们的框架中被捕获。

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引用次数: 0

Swift Markov Logic for Probabilistic Reasoning on Knowledge Graphs 知识图概率推理的快速马尔可夫逻辑

IF 1.4 2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2022-11-09 DOI: 10.1017/s1471068422000412

LUIGI BELLOMARINI, ELEONORA LAURENZA, EMANUEL SALLINGER, EVGENY SHERKHONOV

We provide a framework for probabilistic reasoning in Vadalog-based Knowledge Graphs (KGs), satisfying the requirements of ontological reasoning: full recursion, powerful existential quantification, expression of inductive definitions. Vadalog is a Knowledge Representation and Reasoning (KRR) language based on Warded Datalog+/–, a logical core language of existential rules, with a good balance between computational complexity and expressive power. Handling uncertainty is essential for reasoning with KGs. Yet Vadalog and Warded Datalog+/– are not covered by the existing probabilistic logic programming and statistical relational learning approaches for several reasons, including insufficient support for recursion with existential quantification and the impossibility to express inductive definitions. In this work, we introduce Soft Vadalog, a probabilistic extension to Vadalog, satisfying these desiderata. A Soft Vadalog program induces what we call a Probabilistic Knowledge Graph (PKG), which consists of a probability distribution on a network of chase instances, structures obtained by grounding the rules over a database using the chase procedure. We exploit PKGs for probabilistic marginal inference. We discuss the theory and present MCMC-chase, a Monte Carlo method to use Soft Vadalog in practice. We apply our framework to solve data management and industrial problems and experimentally evaluate it in the Vadalog system.

我们提供了一个基于vadalog知识图的概率推理框架，满足了本体论推理的要求:完全递归、强大的存在量化、归纳定义的表达。Vadalog是一种基于存在规则的逻辑核心语言——warddatalog +/ -的知识表示和推理(Knowledge Representation and Reasoning, KRR)语言，在计算复杂性和表达能力之间取得了很好的平衡。处理不确定性对于使用KGs进行推理至关重要，然而Vadalog和warddatalog +/ -并没有被现有的概率逻辑规划和统计关系学习方法所涵盖，原因有几个，包括对存在量化递归的支持不足，以及无法表达归纳定义。在这项工作中，我们引入了软Vadalog，一种Vadalog的概率扩展，满足了这些需求。软Vadalog程序产生了我们所说的概率知识图(PKG)，它由追逐实例网络上的概率分布组成，该网络结构是通过使用追逐过程在数据库上建立规则而获得的。我们利用pkg进行概率边际推断。讨论了软Vadalog的基本原理，提出了一种蒙特卡罗方法MCMC-chase。我们将该框架应用于解决数据管理和工业问题，并在Vadalog系统中进行了实验评估。

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引用次数: 0

An Application of a Runtime Epistemic Probabilistic Event Calculus to Decision-making in e-Health Systems 运行时认知概率事件演算在电子医疗系统决策中的应用

IF 1.4 2区数学 Q2 Computer Science

Theory and Practice of Logic Programming

Pub Date : 2022-10-20 DOI: 10.1017/s1471068422000382

FABIO AURELIO D’ASARO, LUCA RAGGIOLI, SALIM MALEK, MARCO GRAZIOSO, SILVIA ROSSI

We present and discuss a runtime architecture that integrates sensorial data and classifiers with a logic-based decision-making system in the context of an e-Health system for the rehabilitation of children with neuromotor disorders. In this application, children perform a rehabilitation task in the form of games. The main aim of the system is to derive a set of parameters the child’s current level of cognitive and behavioral performance (e.g., engagement, attention, task accuracy) from the available sensors and classifiers (e.g., eye trackers, motion sensors, emotion recognition techniques) and take decisions accordingly. These decisions are typically aimed at improving the child’s performance by triggering appropriate re-engagement stimuli when their attention is low, by changing the game or making it more difficult when the child is losing interest in the task as it is too easy. Alongside state-of-the-art techniques for emotion recognition and head pose estimation, we use a runtime variant of a probabilistic and epistemic logic programming dialect of the Event Calculus, known as the Epistemic Probabilistic Event Calculus. In particular, the probabilistic component of this symbolic framework allows for a natural interface with the machine learning techniques. We overview the architecture and its components, and show some of its characteristics through a discussion of a running example and experiments.

我们提出并讨论了一种运行时架构，该架构将感官数据和分类器与基于逻辑的决策系统集成在电子健康系统的背景下，用于神经运动障碍儿童的康复。在这个应用程序中，孩子们以游戏的形式执行康复任务。该系统的主要目的是从可用的传感器和分类器(例如眼动仪、运动传感器、情绪识别技术)中得出儿童当前认知和行为表现水平的一组参数(例如，参与度、注意力、任务准确性)，并据此做出决定。这些决定通常是为了提高孩子的表现，当他们注意力不集中时，通过触发适当的重新参与刺激，当孩子对任务失去兴趣时，通过改变游戏或增加难度，因为任务太简单了。除了最先进的情感识别和头部姿势估计技术外，我们还使用事件演算的概率和认知逻辑编程方言的运行时变体，称为认知概率事件演算。特别是，这个符号框架的概率成分允许与机器学习技术的自然接口。我们概述了该体系结构及其组件，并通过对运行示例和实验的讨论展示了它的一些特征。

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