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Modeling and reasoning in event calculus using goal-directed constraint answer set programming

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arXiv 2021年

作者： Arias, Joaquín Carro, Manuel Chen, Zhuo Gupta, Gopal CETINIA Universidad Rey Juan Carlos IMDEA Software Institute Universidad Politécnica de Madrid University of Texas Dallas United States

Automated commonsense reasoning is essential for building human-like AI systems featuring, for example, explainable AI. Event Calculus (EC) is a family of formalisms that model commonsense reasoning with a sound, logical basis. Previous attempts to mechanize reasoning using EC faced difficulties in the treatment of the continuous change in dense domains (e.g., time and other physical quantities), constraints among variables, default negation, and the uniform application of different inference methods, among others. We propose the use of s(CASP), a query-driven, top-down execution model for Predicate Answer Set programming with Constraints, to model and reason using EC. We show how EC scenarios can be naturally and directly encoded in s(CASP) and how it enables deductive and abductive reasoning tasks in domains featuring constraints involving both dense time and dense fluents. Under consideration in theory and practice of logic programming (TPLP). © 2021, CC BY.

关键词： Calculations

Ontoscene, a logic-based scene interpreter: Implementation and application in the rock art domain

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arXiv 2019年

作者： BRIOLA, DANIELA MASCARDI, VIVIANA GIOSEFFI, MASSIMILIANO Department of Computer Sciences Systems and Communications University of Milano Bicocca Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Italy

We present OntoScene, a framework aimed at understanding the semantics of visual scenes starting from the semantics of their elements and the spatial relations holding between them. OntoScene exploits ontologies for representing knowledge and Prolog for specifying the interpretation rules that domain experts may adopt, and for implementing the SceneInterpreter engine. Ontologies allow the designer to formalize the domain in a reusable way, and make the system modular and interoperable with existing multiagent systems, while Prolog provides a solid basis to define complex rules of interpretation in a way that can be affordable even for people with no background in Computational logics. The domain selected for experimenting OntoScene is that of prehistoric rock art, which provides us with a fascinating and challenging testbed. Under consideration in theory and practice of logic programming (TPLP). Copyright © 2019, The Authors. All rights reserved.

关键词： Ontology

CoLoSL: Concurrent local subjective logic

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2015年 9032卷 710-735页

作者： Raad, Azalea Villard, Jules Gardner, Philippa Imperial College London United Kingdom

ISBN: (纸本)9783662466681

A key difficulty in verifying shared-memory concurrent programs is reasoning compositionally about each thread in isolation. Existing verification techniques for fine-grained concurrency typically require reasoning about either the entire shared state or disjoint parts of the shared state, impeding compositionality. This paper introduces the program logic CoLoSL, where each thread is verified with respect to its subjective view of the global shared state. This subjective view describes only that part of the state accessed by the thread. Subjective views may arbitrarily overlap with each other, and expand and contract depending on the resource required by the thread. This flexibility gives rise to small specifications and, hence, more compositional reasoning for concurrent programs. We demonstrate our reasoning on a range of examples, including a concurrent computation of a spanning tree of a graph. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Computer circuits

Reasoning on DL-LiteR with Defeasibility in ASP

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arXiv 2021年

作者： Bozzato, Loris Eiter, Thomas Serafini, Luciano Fondazione Bruno Kessler Via Sommarive 18 Trento38123 Italy Technische Universität Wien Favoritenstraße 9-11 ViennaA-1040 Austria

Reasoning on defeasible knowledge is a topic of interest in the area of description logics, as it is related to the need of representing exceptional instances in knowledge bases. In this direction, in our previous works we presented a framework for representing (contextualized) OWL RL knowledge bases with a notion of justified exceptions on defeasible axioms: reasoning in such framework is realized by a translation into ASP programs. The resulting reasoning process for OWL RL, however, introduces a complex encoding in order to capture reasoning on the negative information needed for reasoning on exceptions. In this paper, we apply the justified exception approach to knowledge bases in DL-LiteR, i.e., the language underlying OWL QL. We provide a definition for DL-LiteR knowledge bases with defeasible axioms and study their semantic and computational properties. In particular, we study the effects of exceptions over unnamed individuals. The limited form of DL-LiteR axioms allows us to formulate a simpler ASP encoding, where reasoning on negative information is managed by direct rules. The resulting materialization method gives rise to a complete reasoning procedure for instance checking in DL-LiteR with defeasible axioms. Under consideration in theory and practice of logic programming (TPLP). Copyright © 2021, The Authors. All rights reserved.

关键词： logic programming

Reasoning on Multi-Relational Contextual Hierarchies via Answer Set programming with Algebraic Measures

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arXiv 2021年

作者： Bozzato, Loris Eiter, Thomas Kiesel, Rafael Fondazione Bruno Kessler Via Sommarive 18 Trento38123 Italy Technische Universität Wien Favoritenstraße 9-11 ViennaA-1040 Austria

Dealing with context dependent knowledge has led to different formalizations of the notion of context. Among them is the Contextualized Knowledge Repository (CKR) framework, which is rooted in description logics but links on the reasoning side strongly to logic programs and Answer Set programming (ASP) in particular. The CKR framework caters for reasoning with defeasible axioms and exceptions in contexts, which was extended to knowledge inheritance across contexts in a coverage (specificity) hierarchy. However, the approach supports only this single type of contextual relation and the reasoning procedures work only for restricted hierarchies, due to non-trivial issues with model preference under exceptions. In this paper, we overcome these limitations and present a generalization of CKR hierarchies to multiple contextual relations, along with their interpretation of defeasible axioms and preference. To support reasoning, we use ASP with algebraic measures, which is a recent extension of ASP with weighted formulas over semirings that allows one to associate quantities with interpretations depending on the truth values of propositional atoms. Notably, we show that for a relevant fragment of CKR hierarchies with multiple contextual relations, query answering can be realized with the popular asprin framework. The algebraic measures approach is more powerful and enables e.g. reasoning with epistemic queries over CKRs, which opens interesting perspectives for the use of quantitative ASP extensions in other applications. Under consideration for acceptance in theory and practice of logic programming (TPLP). Copyright © 2021, The Authors. All rights reserved.

关键词： Data description

Building Information Modeling Using Constraint logic programming

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arXiv 2022年

作者： Arias, Joaquín Törmä, Seppo Carro, Manuel Gupta, Gopal CETINIA Universidad Rey Juan Carlos Madrid Spain VisuaLynk Oy Espoo Finland Universidad Politécnica de Madrid Spain IMDEA Software Institute Pozuelo Spain University of Texas at Dallas Richardson United States

Building Information Modeling (BIM) produces three-dimensional object-oriented models of buildings combining the geometrical information with a wide range of properties about materials, products, safety, to name just a few. BIM is slowly but inevitably revolutionizing the architecture, engineering, and construction (AEC) industry. Buildings need to be compliant with regulations about stability, safety, and environmental impact. Manual compliance checking is tedious and error-prone, and amending flaws discovered only at construction time causes huge additional costs and delays. Several tools can check BIM models for conformance with rules/guidelines. For example, Singapore’s CORENET e-Submission System checks fire safety. But since the current BIM exchange format only contains basic information about building objects, a separate, ad-hoc model pre-processing is required to determine, e.g., evacuation routes. Moreover, they face difficulties in adapting existing built-in rules and/or adding new ones (to cater for building regulations, that can vary not only among countries but also among parts of the same city), if at all possible. We propose the use of logic-based executable formalisms (CLP and Constraint ASP) to couple BIM models with advanced knowledge representation and reasoning capabilities. Previous experience shows that such formalisms can be used to uniformly capture and reason with knowledge (including ambiguity) in a large variety of domains. Additionally, incorporating checking within design tools makes it possible to ensure that models are rule-compliant at every step. This also prevents erroneous designs from having to be (partially) redone, which is also costly and burdensome. To validate our proposal, we implemented a preliminary reasoner under CLP(Q/R) and ASP with constraints and evaluated it with several BIM models. Under consideration for acceptance in theory and practice of logic programming (TPLP). © 2022, CC BY.

关键词： logic programming

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线性规划的教学

数学的实践与认识 2002年第1期32卷 168-172页

作者：贺祖国王晓霞北京邮电大学理学院北方交通大学理学院北京100044

作者给出了线性规划的一个更为一般的表现形式 ,明确定义了具有标准型形式的线性规划的等价变换 ,使得单纯形法的讲解更清晰简洁 ,便于学生掌握 ,且兼顾了数学形式美和逻辑美的学科特点 ;文中也体现了重视实例式教学的想法 .

关键词：线性规划标准型单形纯表等价变换教学

Generating Global and Local Explanations for Tree-Ensemble Learning Methods by Answer Set programming

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arXiv 2024年

作者： Takemura, Akihiro Inoue, Katsumi The Graduate University for Advanced Studies SOKENDAI Tokyo Japan National Institute of Informatics 2-1-2 Hitotsubashi Chiyoda-ku Tokyo101-8430 Japan

We propose a method for generating rule sets as global and local explanations for tree-ensemble learning methods using Answer Set programming (ASP). To this end, we adopt a decompositional approach where the split structures of the base decision trees are exploited in the construction of rules, which in turn are assessed using pattern mining methods encoded in ASP to extract explanatory rules. For global explanations, candidate rules are chosen from the entire trained tree-ensemble models, whereas for local explanations, candidate rules are selected by only considering rules that are relevant to the particular predicted instance. We show how user-defined constraints and preferences can be represented declaratively in ASP to allow for transparent and flexible rule set generation, and how rules can be used as explanations to help the user better understand the models. Experimental evaluation with real-world datasets and popular tree-ensemble algorithms demonstrates that our approach is applicable to a wide range of classification tasks. Under consideration in theory and practice of logic programming (TPLP). © 2024, CC BY.

关键词： Adversarial machine learning

IASCAR: Incremental Answer Set Counting by Anytime Refinement

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arXiv 2023年

作者： Fichte, Johannes K. Gaggl, Sarah Alice Hecher, Markus Rusovac, Dominik Sweden TU Dresden Logic Programming and Argumentation Group Germany Massachusetts Institute of Technology United States

Answer set programming (ASP) is a popular declarative programming paradigm with various applications. Programs can easily have many answer sets that cannot be enumerated in practice, but counting still allows quantifying solution spaces. If one counts under assumptions on literals, one obtains a tool to comprehend parts of the solution space, so-called answer set navigation. However, navigating through parts of the solution space requires counting many times, which is expensive in theory. Knowledge compilation compiles instances into representations on which counting works in polynomial time. However, these techniques exist only for CNF formulas, and compiling ASP programs into CNF formulas can introduce an exponential overhead. This paper introduces a technique to iteratively count answer sets under assumptions on knowledge compilations of CNFs that encode supported models. Our anytime technique uses the inclusion-exclusion principle to improve bounds by over- and undercounting systematically. In a preliminary empirical analysis, we demonstrate promising results. After compiling the input (offline phase), our approach quickly (re)counts. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods