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An efficient propositional system for abductive logic programming

ARTIFICIAL INTELLIGENCE REVIEW 2024年第12期57卷 334页

作者： Gavanelli, Marco Julian-Iranzo, Pascual Saenz-Perez, Fernando Univ Ferrara Dept Engn Ferrara Italy Univ Castilla La Mancha Dept Informat Technol & Syst Ciudad Real Spain Univ Complutense Madrid Dept Software Engn & Artificial Intelligence Madrid Spain

abductive logic programming (ALP) extends logic programming with hypothetical reasoning by means of abducibles, an extension able to handle interesting problems, such as diagnosis, planning, and verification with formal methods. Implementations of this extension have been using Prolog meta-interpreters and Prolog programs with Constraint Handling Rules (CHR). While the latter adds a clean and efficient interface to the host system, it still suffers in performance for large programs. Here, the concern is to obtain a more performant implementation of the SCIFF system following a compiled approach. This paper, as a first step in this long term goal, sets out a propositional ALP system following SCIFF, eliminating the need for CHR and achieving better performance.

关键词： abductive logic programming SCIFF Hypothetical Reasoning System Implementation

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Accountable Protocols in abductive logic programming

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ACM TRANSACTIONS ON INTERNET TECHNOLOGY 2018年第4期18卷 1–20页

作者： Gavanelli, Marco Alberti, Marco Lamma, Evelina Univ Ferrara ENDIF Dept Engn Via G Saragat 1 I-44122 Ferrara Italy Univ Ferrara DMI Via G Saragat 1 I-44122 Ferrara Italy

Finding the entity responsible for an unpleasant situation is often difficult, especially in artificial agent societies. SCIFF is a formalization of agent societies, including a language to describe rules and protocols, and an abductive proof procedure for compliance checking. However, how to identify the entity responsible for a violation is not always clear. In this work, a definition of accountability for artificial societies is formalized in SCIFF. Two tools are provided for the designer of interaction protocols: a guideline, in terms of syntactic features that ensure accountability of the protocol, and an algorithm (implemented in a software tool) to investigate if, for a given protocol, nonaccountability issues could arise.

关键词： SCIFF accountability abductive logic programming

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Evaluating Compliance: From LTL to abductive logic programming

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FUNDAMENTA INFORMATICAE 2018年第1-2期159卷 35-63页

作者： Chesani, Federico Gavanelli, Marco Lamma, Evelina Mello, Paola Montali, Marco Univ Bologna Vle Risorgimento 2 I-40136 Bologna Italy Univ Ferrara Via Saragat 1 I-44122 Ferrara Italy Free Univ Bozen Bolzano Piazza Domenicani 3 I-39100 Bolzano Italy

The compliance verification task amounts to establishing if the execution of a system, given in terms of observed happened events, does respect a given property. In the past both the frameworks of Temporal logics and logic programming have been extensively exploited to assess compliance in different domains, such as normative multi-agent systems, business process management and service oriented computing. In this work we review the LTL and SCIFF frameworks in the light of compliance evaluation, and formally investigate the relationship between the two approaches. We define a notion of compliance within each approach, and then we show that an arbitrary LTL formula can be expressed in SCIFF, by providing a translation procedure from LTL to SCIFF which preserves compliance.

关键词： Linear Temporal logic abductive logic programming Compliance Verification

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Extending expressivity and flexibility of abductive logic programming

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JOURNAL OF INTELLIGENT INFORMATION SYSTEMS 2018年第3期51卷 647-672页

作者： Ferilli, Stefano Univ Bari Dipartimento Informat Bari Italy Univ Bari Ctr Interdipartimentale Log & Sue Applicaz Bari Italy

Real-world problems often require purely deductive reasoning to be supported by other techniques that can cope with noise in the form of incomplete and uncertain data. abductive inference tackles incompleteness by guessing unknown information, provided that it is compliant with given constraints. Probabilistic reasoning tackles uncertainty by weakening the sharp logical approach. This work aims at bringing both together and at further extending the expressive power of the resulting framework, called Probabilistic Expressive abductive logic programming (PEALP). It adopts a logic programming perspective, introducing several kinds of constraints and allowing to set a degree of strength on their validity. Procedures to handle both extensions, compatibly with standard abductive and probabilistic frameworks, are also provided.

关键词： abductive logic programming Probability Constraints

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Evaluating Compliance: From LTL to abductive logic programming

Evaluating Compliance: From LTL to Abductive Logic Programmi...

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Fundamenta Informaticae

作者： Chesani, Federico Gavanelli, Marco Lamma, Evelina Mello, Paola Montali, Marco University of Bologna V.le Risorgimento 2 Bologna40136 Italy University of Ferrara Via Saragat 1 Ferrara44122 Italy Free Universty of Bozen-Bolzano Piazza Domenicani 3 BolzanoI-39100 Italy

关键词： Compliance control Administrative data processing Computer circuits Distributed computer systems Enterprise resource management logic programming Multi agent systems Temporal logic abductive logic programming Business process management Compliance evaluations Compliance verification Linear temporal logic Normative Multi Agent Systems Service oriented computing Translation procedures

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Reasoning on Datalog±Ontologies with abductive logic programming

Reasoning on Datalog±Ontologies with Abductive Logic Progra...

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Fundamenta Informaticae

作者： Gavanelli, Marco Lamma, Evelina Riguzzi, Fabrizio Bellodi, Elena Zese, Riccardo Cota, Giuseppe Dipartimento di Ingegneria University of Ferrara Italy Dipartimento di Matematica e Informatica University of Ferrara Italy

Ontologies form the basis of the Semantic Web. Description logics (DLs) are often the languages of choice for modeling ontologies. Integration of DLs with rules and rule-based reasoning is crucial in the so-called Semantic Web stack vision - a complete stack of recommendations and languages each based on and/or exploiting the underlying layers - which adds new features to the standards used in theWeb. The growing importance of the integration between DLs and rules is proved by the definition of the profile OWL 2 RL1and the definition of languages such as RIF2and SWRL3. Datalog±is an extension of Datalog which can be used for representing lightweight ontologies and expressing some languages of the DL-Lite family, with tractable query answering under certain language restrictions. In particular, it is able to express the DL-Lite version defined in OWL. In this work, we show that abductive logic programming (ALP) can be used to represent Datalog±ontologies, supporting query answering through an abductive proof procedure, and smoothly achieving the integration of ontologies and rule-based reasoning. Often, reasoning with DLs means finding explanations for the truth of queries, that are useful when debugging ontologies and to understand answers given by the reasoning process. We show that reasoning under existential rules can be expressed by ALP languages and we present a solving system, which is experimentally proved to be competitive with DL reasoning systems. In particular, we consider an ALP framework named SCIFF derived from the IFF abductive framework. Forward and backward reasoning is naturally supported in this ALP framework. The SCIFF language smoothly supports the integration of rules, expressed in a logic programming language, with Datalog±ontologies, mapped into SCIFF (forward) integrity constraints. The main advantage is that this integration is achieved within a single language, grounded on abduction in computational logic, and able to model existential rul

关键词： Modeling languages Birds Computation theory Computer circuits Data description Integration logic programming Ontology Semantic Web abductive logic programming Computational logic Forward and backward Integrity constraints Lightweight ontology Ontologies and rules Rule based reasoning Underlying layers

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Probabilistic abductive logic programming using Dirichlet priors

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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2016年第0期78卷 223-240页

作者： Turliuc, Calin Rares Dickens, Luke Russo, Alessandra Broda, Krysia Imperial Coll London Dept Comp London England UCL Dept Informat Studies London WC1E 6BT England

Probabilistic programming is an area of research that aims to develop general inference algorithms for probabilistic models expressed as probabilistic programs whose execution corresponds to inferring the parameters of those models. In this paper, we introduce a probabilistic programming language (PPL) based on abductive logic programming for performing inference in probabilistic models involving categorical distributions with Dirichlet priors. We encode these models as abductive logic programs enriched with probabilistic definitions and queries, and show how to execute and compile them to boolean formulas. Using the latter, we perform generalized inference using one of two proposed Markov Chain Monte Carlo (MCMC) sampling algorithms: an adaptation of uncollapsed Gibbs sampling from related work and a novel collapsed Gibbs sampling (CGS). We show that CGS converges faster than the uncollapsed version on a latent Dirichlet allocation (LDA) task using synthetic data. On similar data, we compare our PPL with LDA-specific algorithms and other PPLs. We find that all methods, except one, perform similarly and that the more expressive the PPL, the slower it is. We illustrate applications of our PPL on real data in two variants of LDA models (Seed and Cluster LDA), and in the repeated insertion model (RIM). In the latter, our PPL yields similar conclusions to inference with EM for Mallows models. (C) 2016 The Author(s). Published by Elsevier Inc.

关键词： Probabilistic programming abductive logic programming Markov Chain Monte Carlo Latent Dirichlet allocation Repeated insertion model

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Dischargeable Obligations in the SCIFF Framework

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FUNDAMENTA INFORMATICAE 2020年第3-4期176卷 321-348页

作者： Alberti, Marco Gavanelli, Marco Lamma, Evelina Riguzzi, Fabrizio Satoh, Ken Zese, Riccardo Univ Ferrara Dipartimento Matemat & Informat Via Saragat 1 I-44122 Ferrara Italy Univ Ferrara Dipartimento Ingn Via Saragat 1 I-44122 Ferrara Italy Natl Inst Informat Principles Informat Res Div Chiyoda Ku 2-1-2 Hitotsubashi Tokyo 1018430 Japan

abductive logic programming (ALP) has been proven very effective for formalizing societies of agents, commitments and norms, in particular by mapping the most common deontic operators (obligation, prohibition, permission) to abductive expectations. In our previous works, we have shown that ALP is a suitable framework for representing norms. Normative reasoning and query answering were accommodated by the same abductive proof procedure, named SCIFF. In this work, we introduce a defeasible flavour in this framework, in order to possibly discharge obligations in some scenarios. abductive expectations can also be qualified as dischargeable, in the new, extended syntax. Both declarative and operational semantics are improved accordingly, and proof of soundness is given under syntax allowedness conditions. Moreover, the dischargement itself might be proved invalid, or incoherent with the rules, due to new knowledge provided later on. In such a case, a discharged expectation might be reinstated and hold again after some evidence is given. We extend the notion of dischargement to take into consideration also the reinstatement of expectations. The expressiveness and power of the extended framework, named SCIFFD, is shown by modeling and reasoning upon a fragment of the Japanese Civil Code. In particular, we consider a case study concerning manifestations of intention and their rescission (Section II of the Japanese Civil Code).

关键词： Normative reasoning abductive logic programming Constraint logic programming Dischargement of expectations

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abductive logic programming agents with destructive databases

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2011年第1-2期62卷 129-158页

作者： Kowalski, Robert Sadri, Fariba Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England

In this paper we present an agent language that combines agent functionality with a state transition theory and model-theoretic semantics. The language is based on abductive logic programming (ALP), but employs a simplified state-free syntax, with an operational semantics that uses destructive updates to manipulate a database, which represents the current state of the environment. The language builds upon the ALP combination of logic programs, to represent an agent's beliefs, and integrity constraints, to represent the agent's goals. logic programs are used to define macro-actions, intensional predicates, and plans to reduce goals to sub-goals including actions. Integrity constraints are used to represent reactive rules, which are triggered by the current state of the database and recent agent actions and external events. The execution of actions and the assimilation of observations generate a sequence of database states. In the case of the successful solution of all goals, this sequence, taken as a whole, determines a model that makes the agent's goals and beliefs all true.

关键词： abductive logic programming Agent languages Model-theoretic semantics

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A logic programming Language Designed for the Modeling of abductive Reasoning in an Educational Context 15

A Logic Programming Language Designed for the Modeling of Ab...

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15th Mexican International Conference on Artificial Intelligence (MICAI) - Advances in Artificial Intelligence

作者： de Oliveira, Osvaldo Luiz Oliveira, Carlos Eduardo A. Martins, Ricardo Jose Matsumoto, Marcio FACCAMP Comp Sci Dept Campo Limpo Paulista SP Brazil IFSULDEMINAS Muzambinho MG Brazil IFSP Sao Paulo SP Brazil

ISBN: (纸本)9781538677353

The programming of simulations of real or abstract phenomena is referred to as computational modeling. In the educational sphere, computational modeling is useful for students in learning about a phenomenon via programming activities. abductive logic programming is a computer modeling activity with considerable educational potential due to the universal nature of logic as formalism for modeling;however, existing languages and frameworks of abductive logic programming require students to have a broad knowledge of logic programming, which prevents the use of these solutions in a general educational context. This work proposes a language referred to as Abdl, which has been designed to facilitate abductive logic programming in school environments. This paper describes the Abdl language and how it can be used for computational modeling in an educational context.

关键词： abductive logic programming Computational modeling Artificial Intelligence in education

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