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39th international conference on logic programming workshops, iclp workshops 2023

作者： Bertagnon, Alessandro Gavanelli, Marco Department of Environmental and Prevention Sciences University of Ferrara C.so Ercole I D’Este 32 Ferrara Italy Department of Engineering University of Ferrara Via Saragat 1 Ferrara Italy

the Traveling Salesperson Problem (TSP) is one of the best-known problems in computer science. Many instances and real world applications fall into the Euclidean TSP special case, in which each node is identified by its coordinates on the plane and the Euclidean distance is used as cost function. It is worth noting that in the Euclidean TSP more information is available than in the general case;in a previous publication, the use of geometric information has been exploited to speedup TSP solving for Constraint logic programming (CLP) solvers. In this work, we study the applicability of geometric reasoning to the Euclidean TSP in the context of an ASP computation. We compare experimentally a classical ASP approach to the TSP and the effect of the reasoning based on geometric properties. We also compare the speedup of the additional filtering based on geometric information on an Answer Set programming (ASP) solver and a CLP on Finite Domain (CLP(FD)) solver. 2023 Copyright for this paper by its authors.

关键词： Geometry

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Integrating logic Rules with Everything Else, Seamlessly

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thEORY AND PRACTICE OF logic programming 2023年第4期23卷 678-695页

作者： Liu, Yanhong A. Stoller, Scott D. Tong, Yi Lin, Bo SUNY Stony Brook Stony Brook NY 11794 USA

this paper presents a language, Alda, that supports all of logic rules, sets, functions, updates, and objects as seamlessly integrated built-ins. the key idea is to support predicates in rules as set-valued variables that can be used and updated in any scope, and support queries using rules as either explicit or implicit automatic calls to an inference function. We have defined a formal semantics of the language, implemented a prototype compiler that builds on an object-oriented language that supports concurrent and distributed programming and on an efficient logic rule system, and successfully used the language and implementation on benchmarks and problems from a wide variety of application domains. We describe the compilation method and results of experimental evaluation.

关键词： language design and implementation logic rules sets comprehension aggregation quantification functions updates objects concurrent and distributed

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asymptoticplp: Approximating probabilistic logic programs on large domains 39

asymptoticplp: Approximating probabilistic logic programs on...

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39th international conference on logic programming workshops, iclp workshops 2023

作者： Quach, Bao Loi Weitkämper, Felix Q. Ludwig-Maximilians-Universität München Oettingenstr. 67 München80538 Germany

Probabilistic logic programs are logic programs in which some of the clauses are annotated with probabilistic facts. the behaviour of relations in these clauses can be very complex, leading to scalability issues. Asymptotic representations, in which queries are completely independent of the domain size and which approximate a probabilistic logic program on large domains, allow us to gain an understanding on how a probabilistic logic programs will behave for increasing domain sizes, and can be computed without actually having to execute the logic program. In particular, every probabilistic logic program under the distribution semantics is asymptotically equivalent to an acyclic probabilistic logic program consisting only of determinate clauses over probabilistic facts. We present asymptoticplp, a Prolog implementation of an algorithm which computes this. the transformation proceeds in several, modular steps which are of independent interest. these steps include rewriting the probabilistic logic program to a formula of least fixed point logic and then applying asymptotic quantifier elimination on the formula. Quantifier-free first-order formulas are then rewritten as acyclic determinate stratified DATALOG formulas, which together with the original probabilistic facts form a (probabilistic) logic program. 2023 Copyright for this paper by its authors.

关键词： Semantics

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NeSyFOLD: Extracting logic Programs from Convolutional Neural Networks 39

NeSyFOLD: Extracting Logic Programs from Convolutional Neura...

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39th international conference on logic programming workshops, iclp workshops 2023

作者： Padalkar, Parth Wang, Huaduo Gupta, Gopal University of Texas at Dallas Richardson United States

We present a novel neurosymbolic framework called NeSyFOLD to extract logic rules from a CNN and create a NeSyFOLD model to classify images. NeSyFOLD’s learning pipeline is as follows: (i) We first pre-train a CNN on the input image dataset and extract activations of the last layer kernels as binary values;(ii) Next, we use the FOLD-SE-M rule-based machine learning algorithm to generate a logic program that can classify an image—represented as a vector of binary activations corresponding to each kernel—while producing a logical explanation. the rules generated by the FOLD-SE-M algorithm have kernel numbers as predicates. We have devised a novel algorithm for automatically mapping the CNN kernels to semantic concepts in the images. this mapping is used to replace predicate names (kernel numbers) in the rule-set with corresponding semantic concept labels. the resulting rule-set is interpretable, and can be intuitively understood by humans. We compare our NeSyFOLD framework with the ERIC system that uses a decision-tree like algorithm to obtain the rules. Our framework has the following advantages over ERIC: (i) In most cases, NeSyFOLD generates smaller rule-sets without compromising on the accuracy and fidelity;(ii) NeSyFOLD generates the mapping of filter numbers to semantic labels automatically. 2023 Copyright for this paper by its authors.

关键词： Mapping

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Beyond logic programming for Legal Reasoning 39

Beyond Logic Programming for Legal Reasoning

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39th international conference on logic programming workshops, iclp workshops 2023

作者： Nguyen, Ha thanh Toni, Francesca Stathis, Kostas Satoh, Ken 2-1-2 Hitotsubashi Chiyoda City Tokyo Japan Imperial College London Exhibition Rd South Kensington LondonSW7 2BX United Kingdom Royal Holloway University of London Egham Hill EghamTW20 0EX United Kingdom

logic programming has long being advocated for legal reasoning, and several approaches have been put forward relying upon explicit representation of the law in logic programming terms. In this position paper we focus on the PROLEG logic-programming-based framework for formalizing and reasoning with Japanese presupposed ultimate fact theory. Specifically, we examine challenges and opportunities in leveraging deep learning techniques for improving legal reasoning using PROLEG, identifying four distinct options ranging from enhancing fact extraction using deep learning to end-to-end solutions for reasoning with textual legal descriptions. We assess advantages and limitations of each option, considering their technical feasibility, interpretability, and alignment with the needs of legal practitioners and decision-makers. We believe that our analysis can serve as a guideline for developers aiming to build effective decision-support systems for the legal domain, while fostering a deeper understanding of challenges and potential advancements by neuro-symbolic approaches in legal applications. 2023 Copyright for this paper by its authors.

关键词： logic programming

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Explanation Graphs for Stable Models of Labelled logic Programs 39

Explanation Graphs for Stable Models of Labelled Logic Progr...

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39th international conference on logic programming workshops, iclp workshops 2023

作者： Cabalar, Pedro Muñiz, Brais University of Coruña Spain

In this paper, we introduce the notion of an explanation graph for any model of a logic program. For each true atom in the model, the graph contains a proof that uses program rules represented by rule labels. A model may have zero, one or several explanation graphs: when it has at least one, it is called a justified model. We prove that all stable models are justified whereas, in general, the opposite does not hold, at least for disjunctive programs. With the purpose of just keeping the information that is considered to be salient, we discuss several operations on explanation graphs. these include the removal of incoming or outgoing edges of a node, but also what we define as node forgetting, that is, removing a node while keeping the connectivity of the rest of the graph. then, we explain how these theoretical concepts constitute the foundation of xclingo 2.0, a tool for explainable Answer Set programming (ASP) that uses, in its turn, an ASP encoding to generate explanations. the tool translates the original program into a meta-program that constitutes the core of xclingo 2.0. We explain this encoding and prove its soundness and completeness with respect to explanation graphs. through a practical example, we illustrate the general use of the tool and its input language based on annotations. Finally, we show how critical these annotations can be for designing meaningful, summarised, natural language explanations. 2022 Copyright for this paper by its authors.

关键词： Encoding (symbols)

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Visual Sensemaking Needs Both Vision and Semantics: On logic-Based Declarative Neurosymbolism for Reasoning about Space and Motion 39

Visual Sensemaking Needs Both Vision and Semantics: On Logic...

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39th international conference on logic programming, iclp 2023

作者： Suchan, Jakob Bhatt, Mehul Varadarajan, Srikrishna DLR Germany Örebro University Sweden CoDesign Lab EU Europe

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ABA Learning via ASP 39

ABA Learning via ASP

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39th international conference on logic programming (iclp)

作者： De Angelis, Emanuele Proietti, Maurizio Toni, Francesca CNR IASI Rome Italy Imperial Coll London Dept Comp London England

Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples. We propose a novel method for implementing ABA Learning using Answer Set programming as a way to help guide Rote Learning and generalisation in ABA Learning.

关键词： logic programming

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Natlog: Embedding logic programming into the Python Deep-Learning Ecosystem 39

Natlog: Embedding Logic Programming into the Python Deep-Lea...

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39th international conference on logic programming (iclp)

作者： Tarau, Paul Univ North Texas Denton TX 76205 USA

Driven by expressiveness commonalities of Python and our Python-based embedded logic-based language Natlog, we design high-level interaction patterns between equivalent language constructs and data types on the two sides. By directly connecting generators and backtracking, nested tuples and terms, coroutines and first-class logic engines, reflection and meta-interpretation, we enable logic-based language constructs to access the full power of the Python ecosystem. We show the effectiveness of our design via Natlog apps working as orchestrators for JAX and Pytorch pipelines and as DCG-driven GPT3 and DALL.E prompt generators.

关键词： embedding of logic programming in the Python ecosystem high-level inter-paradigm data exchanges coroutining with logic engines logic-based neuro-symbolic computing logic grammars as prompt-generators for Large Language Models logic-based neural network configuration and training

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Deontic Paradoxes in ASP with Weak Constraints 39

Deontic Paradoxes in ASP with Weak Constraints

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39th international conference on logic programming (iclp)

作者： Hatschka, Christian Ciabattoni, Agata Eiter, thomas TU Wien Inst Log & Computat Vienna Austria

the rise of powerful AI technology for a range of applications that are sensitive to legal, social, and ethical norms demands decision-making support in presence of norms and regulations. Normative reasoning is the realm of deontic logics, that are challenged by well-known benchmark problems (deontic paradoxes), and lack efficient computational tools. In this paper, we use Answer Set programming (ASP) for addressing these shortcomings and showcase how to encode and resolve several well-known deontic paradoxes utilizing weak constraints. By abstracting and generalizing this encoding, we present a methodology for translating normative systems in ASP with weak constraints. this methodology is applied to "ethical" versions of Pac-man, where we obtain a comparable performance with related works, but ethically preferable results.

关键词： logic programming

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