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Evaluating Datalog Tools for Meta-reasoning over OWL 2 QL Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-03-07 HAYA MAJID QURESHI, WOLFGANG FABER
Metamodeling is a general approach to expressing knowledge about classes and properties in an ontology. It is a desirable modeling feature in multiple applications that simplifies the extension and reuse of ontologies. Nevertheless, allowing metamodeling without restrictions is problematic for several reasons, mainly due to undecidability issues. Practical languages, therefore, forbid classes to occur
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Model Explanation via Support Graphs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-02-29 PEDRO CABALAR, BRAIS MUÑIZ
In this note, we introduce the notion of support graph to define explanations for any model of a logic program. An explanation is an acyclic support graph that, for each true atom in the model, induces a proof in terms of program rules represented by labels. A classical model may have zero, one or several explanations: when it has at least one, it is called a justified model. We prove that all stable
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IASCAR: Incremental Answer Set Counting by Anytime Refinement Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-02-21 JOHANNES K. FICHTE, SARAH ALICE GAGGL, MARKUS HECHER, DOMINIK RUSOVAC
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
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Clingraph: A System for ASP-based Visualization Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-02-14 SUSANA HAHN, ORKUNT SABUNCU, TORSTEN SCHAUB, TOBIAS STOLZMANN
We present the Answer Set Programming (ASP)-based visualization tool clingraph, which aims at visualizing various concepts of ASP by means of ASP itself. This idea traces back to the aspviz tool and clingraph redevelops and extends it in the context of modern ASP systems. More precisely, clingraph takes graph specifications in terms of ASP facts and hands them over to the graph visualization system
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Epistemic Logic Programs: A Study of Some Properties Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-02-05 STEFANIA COSTANTINI, ANDREA FORMISANO
Epistemic logic programs (ELPs), extend answer set programming (ASP) with epistemic operators. The semantics of such programs is provided in terms of world views, which are sets of belief sets, that is, syntactically, sets of sets of atoms. Different semantic approaches propose different characterizations of world views. Recent work has introduced semantic properties that should be met by any semantics
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Knowledge-Based Support for Adhesive Selection: Will it Stick? Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-01-31 SIMON VANDEVELDE, JOOST VENNEKENS, JEROEN JORDENS, BART VAN DONINCK, MAARTEN WITTERS
As the popularity of adhesive joints in industry increases, so does the need for tools to support the process of selecting a suitable adhesive. While some such tools already exist, they are either too limited in scope or offer too little flexibility in use. This work presents a more advanced tool, that was developed together with a team of adhesive experts. We first extract the experts’ knowledge about
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Locally Tight Programs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2024-01-19 JORGE FANDINNO, VLADIMIR LIFSCHITZ, NATHAN TEMPLE
Program completion is a translation from the language of logic programs into the language of first-order theories. Its original definition has been extended to programs that include integer arithmetic, accept input, and distinguish between output predicates and auxiliary predicates. For tight programs, that generalization of completion is known to match the stable model semantics, which is the basis
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CNL2ASP: Converting Controlled Natural Language Sentences into ASP Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-12-20 SIMONE CARUSO, CARMINE DODARO, MARCO MARATEA, MARCO MOCHI, FRANCESCO RICCIO
Answer set programming (ASP) is a popular declarative programming language for solving hard combinatorial problems. Although ASP has gained widespread acceptance in academic and industrial contexts, there are certain user groups who may find it more advantageous to employ a higher-level language that closely resembles natural language when specifying ASP programs. In this paper, we propose a novel
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Human Conditional Reasoning in Answer Set Programming Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-12-14 CHIAKI SAKAMA
Given a conditional sentence “${\varphi}\Rightarrow \psi$" (if ${\varphi}$ then $\psi$) and respective facts, four different types of inferences are observed in human reasoning: Affirming the antecedent (AA) (or modus ponens) reasons $\psi$ from ${\varphi}$; affirming the consequent (AC) reasons ${\varphi}$ from $\psi$; denying the antecedent (DA) reasons $\neg\psi$ from $\neg{\varphi}$; and denying
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Querying Incomplete Data: Complexity and Tractability via Datalog and First-Order Rewritings Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-11-28 AMÉLIE GHEERBRANT, LEONID LIBKIN, ALEXANDRA ROGOVA, CRISTINA SIRANGELO
To answer database queries over incomplete data, the gold standard is finding certain answers: those that are true regardless of how incomplete data is interpreted. Such answers can be found efficiently for conjunctive queries and their unions, even in the presence of constraints. With negation added, the problem becomes intractable however. We concentrate on the complexity of certain answers under
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Tau Prolog: A Prolog Interpreter for the Web Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-09-18 JOSÉ A. RIAZA
Tau Prolog is a client-side Prolog interpreter fully implemented in JavaScript, which aims at implementing the ISO Prolog Standard. Tau Prolog has been developed to be used with either Node.js or a browser seamlessly, and therefore, it has been developed following a non-blocking, callback-based approach to avoid blocking web browsers. Taking the best from JavaScript and Prolog, Tau Prolog allows the
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Integrating Logic Rules with Everything Else, Seamlessly Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-09-06 YANHONG A. LIU, SCOTT D. STOLLER, YI TONG, BO LIN
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
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Locksynth: Deriving Synchronization Code for Concurrent Data Structures with ASP Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-09-01 SARAT CHANDRA VARANASI, NEERAJ MITTAL, GOPAL GUPTA
We present Locksynth, a tool that automatically derives synchronization needed for destructive updates to concurrent data structures that involve a constant number of shared heap memory write operations. Locksynth serves as the implementation of our prior work on deriving abstract synchronization code. Designing concurrent data structures involves inferring correct synchronization code starting with
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Compositional Verification in Rewriting Logic Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-08-31 ÓSCAR MARTÍN, ALBERTO VERDEJO, NARCISO MARTÍ-OLIET
In previous work, summarized in this paper, we proposed an operation of parallel composition for rewriting-logic theories, allowing compositional specification of systems and reusability of components. The present paper focuses on compositional verification. We show how the assume/guarantee technique can be transposed to our setting, by giving appropriate definitions of satisfaction based on transition
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Dyadic Existential Rules Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-08-24 GEORG GOTTLOB, MARCO MANNA, CINZIA MARTE
Existential rules form an expressive ${{\textsf{Datalog}}}$-based language to specify ontological knowledge. The presence of existential quantification in rule-heads, however, makes the main reasoning tasks undecidable. To overcome this limitation, in the last two decades, a number of classes of existential rules guaranteeing the decidability of query answering have been proposed. Unfortunately, only
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Implementing Backjumping by Means of Exception Handling Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-08-24 WŁODZIMIERZ DRABENT
We discuss how to implement backjumping (or intelligent backtracking) in Prolog by using the built-ins throw/1 and catch/3. We show that it is impossible in a general case, contrary to a claim that “backjumping is exception handling." We provide two solutions. One works for binary programs; in a general case it imposes a restriction on where backjumping may originate. The other restricts the class
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Querying Data Exchange Settings Beyond Positive Queries Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-08-15 MARCO CALAUTTI, SERGIO GRECO, CRISTIAN MOLINARO, IRINA TRUBITSYNA
Data exchange, the problem of transferring data from a source schema to a target schema, has been studied for several years. The semantics of answering positive queries over the target schema has been defined in early work, but little attention has been paid to more general queries. A few proposals of semantics for more general queries exist but they either do not properly extend the standard semantics
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Interactive Model Expansion in an Observable Environment Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-08-08 PIERRE CARBONNELLE, JOOST VENNEKENS, MARC DENECKER, BART BOGAERTS
Many practical problems can be understood as the search for a state of affairs that extends a fixed partial state of affairs, the environment, while satisfying certain conditions that are formally specified. Such problems are found in, for example, engineering, law or economics. We study this class of problems in a context where some of the relevant information about the environment is not known by
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The Stable Model Semantics of Datalog with Metric Temporal Operators Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-08-02 PRZEMYSŁAW A. WAŁĘGA, DAVID J. TENA CUCALA, BERNARDO CUENCA GRAU, EGOR V. KOSTYLEV
We introduce negation under the stable model semantics in DatalogMTL – a temporal extension of Datalog with metric temporal operators. As a result, we obtain a rule language which combines the power of answer set programming with the temporal dimension provided by metric operators. We show that, in this setting, reasoning becomes undecidable over the rational timeline, and decidable in ${{\rm E}{\small\rm
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Learnability with PAC Semantics for Multi-agent Beliefs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-31 IONELA G. MOCANU, VAISHAK BELLE, BRENDAN JUBA
The tension between deduction and induction is perhaps the most fundamental issue in areas such as philosophy, cognition, and artificial intelligence. In an influential paper, Valiant recognized that the challenge of learning should be integrated with deduction. In particular, he proposed a semantics to capture the quality possessed by the output of probably approximately correct (PAC) learning algorithms
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Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-26 MICHAEL GELFOND, JORGE FANDINNO, EVGENII BALAI
This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. This language is used for accurately and directly formalizing common benchmark examples from the literature of actual causality. A definition of cause is presented and used to analyze the actual causes of changes with respect to sequences of actions representing those examples.
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ASPER: Answer Set Programming Enhanced Neural Network Models for Joint Entity-Relation Extraction Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-25 TRUNG HOANG LE, HUIPING CAO, TRAN CAO SON
A plethora of approaches have been proposed for joint entity-relation (ER) extraction. Most of these methods largely depend on a large amount of manually annotated training data. However, manual data annotation is time-consuming, labor-intensive, and error-prone. Human beings learn using both data (through induction) and knowledge (through deduction). Answer Set Programming (ASP) has been a widely
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Capturing (Optimal) Relaxed Plans with Stable and Supported Models of Logic Programs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-21 MASOOD FEYZBAKHSH RANKOOH, TOMI JANHUNEN
We establish a novel relation between delete-free planning, an important task for the AI planning community also known as relaxed planning, and logic programming. We show that given a planning problem, all subsets of actions that could be ordered to produce relaxed plans for the problem can be bijectively captured with stable models of a logic program describing the corresponding relaxed planning problem
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Logic-Based Benders Decomposition in Answer Set Programming for Chronic Outpatients Scheduling Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-21 PAOLA CAPPANERA, MARCO GAVANELLI, MADDALENA NONATO, MARCO ROMA
In answer set programming (ASP), the user can define declaratively a problem and solve it with efficient solvers; practical applications of ASP are countless and several constraint problems have been successfully solved with ASP. On the other hand, solution time usually grows in a superlinear way (often, exponential) with respect to the size of the instance, which is impractical for large instances
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Toward A Logical Theory Of Fairness and Bias Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-19 VAISHAK BELLE
Fairness in machine learning is of considerable interest in recent years owing to the propensity of algorithms trained on historical data to amplify and perpetuate historical biases. In this paper, we argue for a formal reconstruction of fairness definitions, not so much to replace existing definitions but to ground their application in an epistemic setting and allow for rich environmental modeling
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External Behavior of a Logic Program and Verification of Refactoring Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-18 JORGE FANDINNO, ZACHARY HANSEN, YULIYA LIERLER, VLADIMIR LIFSCHITZ, NATHAN TEMPLE
Refactoring is modifying a program without changing its external behavior. In this paper, we make the concept of external behavior precise for a simple answer set programming language. Then we describe a proof assistant for the task of verifying that refactoring a program in that language is performed correctly.
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On Program Completion, with an Application to the Sum and Product Puzzle Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-18 VLADIMIR LIFSCHITZ
This paper describes a generalization of Clark’s completion that is applicable to logic programs containing arithmetic operations and produces syntactically simple, natural looking formulas. If a set of first-order axioms is equivalent to the completion of a program, then we may be able to find standard models of these axioms by running an answer set solver. As an example, we apply this “reverse completion”
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“What if?” in Probabilistic Logic Programming Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-17 RAFAEL KIESEL, KILIAN RÜCKSCHLOß, FELIX WEITKÄMPER
A ProbLog program is a logic program with facts that only hold with a specified probability. In this contribution, we extend this ProbLog language by the ability to answer “What if” queries. Intuitively, a ProbLog program defines a distribution by solving a system of equations in terms of mutually independent predefined Boolean random variables. In the theory of causality, Judea Pearl proposes a counterfactual
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Knowledge Authoring for Rules and Actions Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-12 YUHENG WANG, PAUL FODOR, MICHAEL KIFER
Knowledge representation and reasoning (KRR) systems describe and reason with complex concepts and relations in the form of facts and rules. Unfortunately, wide deployment of KRR systems runs into the problem that domain experts have great difficulty constructing correct logical representations of their domain knowledge. Knowledge engineers can help with this construction process, but there is a deficit
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An ASP Framework for the Refinement of Authorization and Obligation Policies Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-11 DANIELA INCLEZAN
This paper introduces a framework for assisting policy authors in refining and improving their policies. In particular, we focus on authorization and obligation policies that can be encoded in Gelfond and Lobo’s $\mathscr{AOPL}$ language for policy specification. We propose a framework that detects the statements that make a policy inconsistent, underspecified, or ambiguous with respect to an action
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Non-deterministic Approximation Operators: Ultimate Operators, Semi-equilibrium Semantics, and Aggregates Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-11 JESSE HEYNINCK, BART BOGAERTS
Approximation fixpoint theory (AFT) is an abstract and general algebraic framework for studying the semantics of non-monotonic logics. In recent work, AFT was generalized to non-deterministic operators, that is, operators whose range are sets of elements rather than single elements. In this paper, we make three further contributions to non-deterministic AFT: (1) we define and study ultimate approximations
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Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-10 VITO BARBARA, MASSIMO GUARASCIO, NICOLA LEONE, GIUSEPPE MANCO, ALESSANDRO QUARTA, FRANCESCO RICCA, ETTORE RITACCO
Artificial Intelligence plays a main role in supporting and improving smart manufacturing and Industry 4.0, by enabling the automation of different types of tasks manually performed by domain experts. In particular, assessing the compliance of a product with the relative schematic is a time-consuming and prone-to-error process. In this paper, we address this problem in a specific industrial scenario
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Automatic Differentiation in Prolog Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-06 TOM SCHRIJVERS, BIRTHE VAN DEN BERG, FABRIZIO RIGUZZI
Automatic differentiation (AD) is a range of algorithms to compute the numeric value of a function’s (partial) derivative, where the function is typically given as a computer program or abstract syntax tree. AD has become immensely popular as part of many learning algorithms, notably for neural networks. This paper uses Prolog to systematically derive gradient-based forward- and reverse-mode AD variants
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An Efficient Solver for ASP(Q) Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-05 WOLFGANG FABER, GIUSEPPE MAZZOTTA, FRANCESCO RICCA
Answer Set Programming with Quantifiers ASP(Q) extends Answer Set Programming (ASP) to allow for declarative and modular modeling of problems from the entire polynomial hierarchy. The first implementation of ASP(Q), called QASP, was based on a translation to Quantified Boolean Formulae (QBF) with the aim of exploiting the well-developed and mature QBF-solving technology. However, the implementation
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An Interleaving Semantics of the Timed Concurrent Language for Argumentation to Model Debates and Dialogue Games Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-07-05 STEFANO BISTARELLI, CARLO TATICCHI, MARIA CHIARA MEO
Time is a crucial factor in modelling dynamic behaviours of intelligent agents: activities have a determined temporal duration in a real-world environment, and previous actions influence agents’ behaviour. In this paper, we propose a language for modelling concurrent interaction between agents that also allows the specification of temporal intervals in which particular actions occur. Such a language
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Knowledge-based Reasoning and Learning under Partial Observability in Ad Hoc Teamwork Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-06-26 HASRA DODAMPEGAMA, MOHAN SRIDHARAN
Ad hoc teamwork (AHT) refers to the problem of enabling an agent to collaborate with teammates without prior coordination. State of the art methods in AHT are data-driven, using a large labeled dataset of prior observations to model the behavior of other agent types and to determine the ad hoc agent’s behavior. These methods are computationally expensive, lack transparency, and make it difficult to
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System Predictor: Grounding Size Estimator for Logic Programs under Answer Set Semantics Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-06-22 DANIEL BRESNAHAN, NICHOLAS HIPPEN, YULIYA LIERLER
Answer set programming is a declarative logic programming paradigm geared towards solving difficult combinatorial search problems. While different logic programs can encode the same problem, their performance may vary significantly. It is not always easy to identify which version of the program performs the best. We present the system predictor (and its algorithmic backend) for estimating the grounding
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smProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-05-25 PIETRO TOTIS, LUC DE RAEDT, ANGELIKA KIMMIG
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
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Distributed Subweb Specifications for Traversing the Web Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-04-25 BART BOGAERTS, BAS KETSMAN, YOUNES ZEBOUDJ, HEBA AAMER, RUBEN TAELMAN, RUBEN VERBORGH
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
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Extended High-Utility Pattern Mining: An Answer Set Programming-Based Framework and Applications Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-04-19 FRANCESCO CAUTERUCCIO, GIORGIO TERRACINA
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
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Solving Rehabilitation Scheduling Problems via a Two-Phase ASP Approach Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-04-17 MATTEO CARDELLINI, PAOLO DE NARDI, CARMINE DODARO, GIUSEPPE GALATÀ, ANNA GIARDINI, MARCO MARATEA, IVAN PORRO
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
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Disjunctive Delimited Control Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-04-11 ALEXANDER VANDENBROUCKE, TOM SCHRIJVERS
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
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Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling Theory Pract. Log. Program. (IF 1.4) Pub Date : 2023-01-26 THOMAS EITER, TOBIAS GEIBINGER, NYSRET MUSLIU, JOHANNES OETSCH, PETER SKOČOVSKÝ, DARIA STEPANOVA
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
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Unifying Framework for Optimizations in Non-Boolean Formalisms Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-11-15 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
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Swift Markov Logic for Probabilistic Reasoning on Knowledge Graphs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-11-09 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
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An Application of a Runtime Epistemic Probabilistic Event Calculus to Decision-making in e-Health Systems Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-10-20 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
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On Establishing Robust Consistency in Answer Set Programs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-09-19 ANDRE THEVAPALAN, GABRIELE KERN-ISBERNER
Answer set programs used in real-world applications often require that the program is usable with different input data. This, however, can often lead to contradictory statements and consequently to an inconsistent program. Causes for potential contradictions in a program are conflicting rules. In this paper, we show how to ensure that a program $\mathcal{P}$ remains non-contradictory given any allowed
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Positive Dependency Graphs Revisited Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-08-23 JORGE FANDINNO, VLADIMIR LIFSCHITZ
Theory of stable models is the mathematical basis of answer set programming. Several results in that theory refer to the concept of the positive dependency graph of a logic program. We describe a modification of that concept and show that the new understanding of positive dependency makes it possible to strengthen some of these results.
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Efficient Knowledge Compilation Beyond Weighted Model Counting Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-08-03 RAFAEL KIESEL, PIETRO TOTIS, ANGELIKA KIMMIG
Quantitative extensions of logic programming often require the solution of so called second level inference tasks, that is, problems that involve a third operation, such as maximization or normalization, on top of addition and multiplication, and thus go beyond the well-known weighted or algebraic model counting setting of probabilistic logic programming under the distribution semantics. We introduce
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MV-Datalog+-: Effective Rule-based Reasoning with Uncertain Observations Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-26 MATTHIAS LANZINGER, STEFANO SFERRAZZA, GEORG GOTTLOB
Modern applications combine information from a great variety of sources. Oftentimes, some of these sources, like machine-learning systems, are not strictly binary but associated with some degree of (lack of) confidence in the observation. We propose MV-Datalog and $\mathrm{MV-Datalog}^\pm$ as extensions of Datalog and $\mathrm{Datalog}^\pm$ , respectively, to the fuzzy semantics of infinite-valued
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On the Foundations of Grounding in Answer Set Programming Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-25 ROLAND KAMINSKI, TORSTEN SCHAUB
We provide a comprehensive elaboration of the theoretical foundations of variable instantiation, or grounding, in Answer Set Programming (ASP). Building on the semantics of ASP’s modeling language, we introduce a formal characterization of grounding algorithms in terms of (fixed point) operators. A major role is played by dedicated well-founded operators whose associated models provide semantic guidance
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Analyzing Semantics of Aggregate Answer Set Programming Using Approximation Fixpoint Theory Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-22 LINDE VANBESIEN, MAURICE BRUYNOOGHE, MARC DENECKER
Aggregates provide a concise way to express complex knowledge. The problem of selecting an appropriate formalization of aggregates for answer set programming (ASP) remains unsettled. This paper revisits it from the viewpoint of Approximation Fixpoint Theory (AFT). We introduce an AFT formalization equivalent with the Gelfond–Lifschitz reduct for basic ASP programs and we extend it to handle aggregates
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Building Information Modeling Using Constraint Logic Programming Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-14 JOAQUÍN ARIAS, SEPPO TÖRMÄ, MANUEL CARRO, GOPAL GUPTA
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 industry. Buildings need to be compliant with regulations about stability, safety, and
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A Neuro-Symbolic ASP Pipeline for Visual Question Answering Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-11 THOMAS EITER, NELSON HIGUERA, JOHANNES OETSCH, MICHAEL PRITZ
We present a neuro-symbolic visual question answering (VQA) pipeline for CLEVR, which is a well-known dataset that consists of pictures showing scenes with objects and questions related to them. Our pipeline covers (i) training neural networks for object classification and bounding-box prediction of the CLEVR scenes, (ii) statistical analysis on the distribution of prediction values of the neural networks
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On Nested Justification Systems Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-11 SIMON MARYNISSEN, JESSE HEYNINCK, BART BOGAERTS, MARC DENECKER
Justification theory is a general framework for the definition of semantics of rule-based languages that has a high explanatory potential. Nested justification systems, first introduced by Denecker et al., allow for the composition of justification systems. This notion of nesting thus enables the modular definition of semantics of rule-based languages, and increases the representational capacities
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Verifying Catamorphism-Based Contracts using Constrained Horn Clauses Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-07 EMANUELE DE ANGELIS, MAURIZIO PROIETTI, FABIO FIORAVANTI, ALBERTO PETTOROSSI
We address the problem of verifying that the functions of a program meet their contracts, specified by pre/postconditions. We follow an approach based on constrained Horn clauses (CHCs) by which the verification problem is reduced to the problem of checking satisfiability of a set of clauses derived from the given program and contracts. We consider programs that manipulate algebraic data types (ADTs)
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An ASP Approach for Reasoning on Neural Networks under a Finitely Many-Valued Semantics for Weighted Conditional Knowledge Bases Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-05 LAURA GIORDANO, DANIELE THESEIDER DUPRÉ
Weighted knowledge bases for description logics with typicality have been recently considered under a “concept-wise” multipreference semantics (in both the two-valued and fuzzy case), as the basis of a logical semantics of multilayer perceptrons (MLPs). In this paper we consider weighted conditional $\mathcal{ALC}$ knowledge bases with typicality in the finitely many-valued case, through three different
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From Logic to Functional Logic Programs Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-04 MICHAEL HANUS
Logic programming is a flexible programming paradigm due to the use of predicates without a fixed data flow. To extend logic languages with the compact notation of functional programming, there are various proposals to map evaluable functions into predicates in order to stay in the logic programming framework. Since amalgamated functional logic languages offer flexible as well as efficient evaluation
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Problem Decomposition and Multi-shot ASP Solving for Job-shop Scheduling Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-04 MOHAMMED M. S. EL-KHOLANY, MARTIN GEBSER, KONSTANTIN SCHEKOTIHIN
Scheduling methods are important for effective production and logistics management, where tasks need to be allocated and performed with limited resources. In particular, the Job-shop Scheduling Problem (JSP) is a well known and challenging combinatorial optimization problem in which tasks sharing a machine are to be arranged in a sequence such that encompassing jobs can be completed as early as possible
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FOLD-RM: A Scalable, Efficient, and Explainable Inductive Learning Algorithm for Multi-Category Classification of Mixed Data Theory Pract. Log. Program. (IF 1.4) Pub Date : 2022-07-01 HUADUO WANG, FARHAD SHAKERIN, GOPAL GUPTA
FOLD-RM is an automated inductive learning algorithm for learning default rules for mixed (numerical and categorical) data. It generates an (explainable) answer set programming (ASP) rule set for multi-category classification tasks while maintaining efficiency and scalability. The FOLD-RM algorithm is competitive in performance with the widely used, state-of-the-art algorithms such as XGBoost and multi-layer