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Query answering in resource-based answer set semantics

THEORY AND PRACTICE OF LOGIC programming 2016年第5-6期16卷 619-635页

作者： Costantini, Stefania Formisano, Andrea Univ Aquila DISIM I-67100 Laquila Italy Univ Perugia DMI GNCS INdAM I-06100 Perugia Italy

In recent work we defined resource-based answer set semantics, which is an extension to answer set semantics stemming from the study of its relationship with linear logic. In fact, the name of the new semantics comes from the fact that in the linear-logic formulation every literal (including negative ones) were considered as a resource. In this paper, we propose a query-answering procedure reminiscent of Prolog for answer set programs under this extended semantics as an extension of XSB-resolution for logic programs with negation.(1) We prove formal properties of the proposed procedure. Under consideration for acceptance in TPLP.

关键词： answer set programming Procedural Semantics Top-down Query-answering

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Fostering the Use of Declarative Formalisms for Real-World Applications: The EmbASP Framework

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NEW GENERATION COMPUTING 2019年第1期37卷 29-65页

作者： Calimeri, Francesco Fusca, Davide Germano, Stefano Perri, Simona Zangari, Jessica Univ Calabria Dept Math & Comp Sci Arcavacata Di Rende Italy

Thanks to a number of efficient implementations, the use of logic formalisms for problem-solving has been increased in several real-world domains. This is the case, for instance, of action languages, such as planning domain definition language (PDDL), or answer set programming (ASP), which is a well-established declarative problem-solving paradigm that became widely used in AI and recognized as a powerful tool for knowledge representation and reasoning (KRR). As the application scenarios widened, the need for proper development tools and interoperability mechanisms for easing interaction and integration between declarative logic-based systems and external systems clearly emerged. In this work, we present a framework for integrating the KRR capabilities of, possibly more than one, declarative formalisms into generic applications developed by means of different programming paradigms. We show the use of the framework by illustrating proper specializations for two formalisms, namely ASP and PDDL, along with specializations for some relevant systems over different platforms, including the mobile setting.

关键词： Artificial intelligence Declarative programming answer set programming Software engineering Applications

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Domain expansion for ASP-programs with external sources

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ARTIFICIAL INTELLIGENCE 2016年 233卷 84-121页

作者： Eiter, Thomas Fink, Michael Krennwallner, Thomas Redl, Christoph Vienna Univ Technol Inst Informat Syst Favoritenstr 9-11 A-1040 Vienna Austria

answer set programming (ASP) is a popular approach to declarative problem solving which for broader usability has been equipped with external source access. The latter may introduce new constants to the program (known as value invention), which can lead to infinite answer sets and non-termination;to prevent this, syntactic safety conditions on programs are common which considerably limit expressiveness (in particular, recursion). We present liberal domain-expansion (Ide) safe programs, a novel generic class of ASP programs with external source access and value invention that enjoy finite restrictability, i.e., equivalence to a finite ground version. They use term bounding functions as a parametric notion of safety, which can be instantiated with syntactic, semantic or combined safety criteria;this empowers us to generalize and integrate many other notions of safety from the literature, and modular composition of criteria makes future extensions easy. Furthermore, we devise a grounding algorithm for lde-safe programs which in contrast to traditional algorithms can ground any such program directly without the need for program decomposition. While we present our approach on top of a proposed formalism in order to make the formalization precise, the general concepts carry over to related formalisms and important special cases as well. An experimental evaluation of Ide-safety on various applications confirms the practicability of our approach. (C) 2016 Elsevier B.V. All rights reserved.

关键词： answer set programming Knowledge representation formalisms Nonmonotonic reasoning External source access Grounding Computational logic

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A systematic analysis of levels of integration between high-level task planning and low-level feasibility checks

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AI COMMUNICATIONS 2016年第2期29卷 319-349页

作者： Erdem, Esra Patoglu, Volkan Schuller, Peter Sabanci Univ Comp Sci & Engn Fac Engn & Nat Sci Istanbul Turkey Sabanci Univ Fac Engn & Nat Sci Mechatron Engn Istanbul Turkey Marmara Univ Dept Comp Engn Istanbul Turkey

We provide a systematic analysis of levels of integration between discrete high-level reasoning and continuous low-level feasibility checks to address hybrid planning problems in robotic applications. We identify four distinct strategies for such an integration: (i) low-level checks are done for all possible cases in advance and the results are used during plan generation;(ii) low-level checks are done exactly when they are needed during the search for a plan;(iii) low-level checks are done after a plan is computed, and if the plan is found infeasible then a new plan is computed;(iv) similar to the previous strategy but the results of previous low-level checks are used during computation of a new plan. We analyze the usefulness of these strategies and their combinations by experiments on hybrid planning problems in different robotic application domains, in terms of computational efficiency and plan quality (relative to its feasibility).

关键词： Task planning motion planning hybrid planning knowledge representation and reasoning answer set programming cognitive robotics experimental analysis

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Thirty years of Epistemic Specifications

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THEORY AND PRACTICE OF LOGIC programming 2022年第6期22卷 1043-1083页

作者： Fandinno, Jorge Faber, Wolfgang Gelfond, Michael Univ Nebraska Omaha Omaha NE 68182 USA Univ Potsdam Potsdam Germany Alpen Adria Univ Klagenfurt Klagenfurt Austria Texas Tech Univ Lubbock TX 79409 USA

The language of epistemic specifications and epistemic logic programs extends disjunctive logic programs under the stable model semantics with modal constructs called subjective literals. Using subjective literals, it is possible to check whether a regular literal is true in every or some stable models of the program, those models, in this context also called belief sets, being collected in a set called world view. This allows for representing, within the language, whether some proposition should be understood accordingly to the open or the closed world assumption. Several attempts for capturing the intuitions underlying the language by means of a formal semantics were given, resulting in a multitude of proposals that makes it difficult to understand the current state of the art. In this article, we provide an overview of the inception of the field and the knowledge representation and reasoning tasks it is suitable for. We also provide a detailed analysis of properties of proposed semantics, and an outlook of challenges to be tackled by future research in the area.

关键词： answer set programming epistemic logic programs epistemic specifications epistemic reasoning autopistemic logic

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Computing maximal and minimal trap spaces of Boolean networks

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NATURAL COMPUTING 2015年第4期14卷 535-544页

作者： Klarner, Hannes Bockmayr, Alexander Siebert, Heike Free Univ Berlin FB Math & Informat D-14195 Berlin Germany

Asymptotic behaviors are often of particular interest when analyzing Boolean networks that represent biological systems such as signal transduction or gene regulatory networks. Methods based on a generalization of the steady state notion, the so-called trap spaces, can be exploited to investigate attractor properties as well as for model reduction techniques. In this paper, we propose a novel optimization-based method for computing all minimal and maximal trap spaces and motivate their use. In particular, we add a new result yielding a lower bound for the number of cyclic attractors and illustrate the methods with a study of a MAPK pathway model. To test the efficiency and scalability of the method, we compare the performance of the ILP solver gurobi with the ASP solver potassco in a benchmark of random networks.

关键词： Boolean networks Attractors Signal transduction Gene regulation answer set programming Integer linear programming

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Inverse reinforcement learning through logic constraint inference

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MACHINE LEARNING 2023年第7期112卷 2593-2618页

作者： Baert, Mattijs Leroux, Sam Simoens, Pieter Univ Ghent imec Dept Informat Technol IDLab Technol pk 126 B-9052 Ghent Belgium

Autonomous robots start to be integrated in human environments where explicit and implicit social norms guide the behavior of all agents. To assure safety and predictability, these artificial agents should act in accordance with the applicable social norms. However, it is not straightforward to define these rules and incorporate them in an agent's policy. Particularly because social norms are often implicit and environment specific. In this paper, we propose a novel iterative approach to extract a set of rules from observed human trajectories. This hybrid method combines the strengths of inverse reinforcement learning and inductive logic programming. We experimentally show how our method successfully induces a compact logic program which represents the behavioral constraints applicable in a Tower of Hanoi and a traffic simulator environment. The induced program is adopted as prior knowledge by a model-free reinforcement learning agent to speed up training and prevent any social norm violation during exploration and deployment. Moreover, expressing norms as a logic program provides improved interpretability, which is an important pillar in the design of safe artificial agents, as well as transferability to similar environments.

关键词： Inductive logic programming Inverse reinforcement learning answer set programming Constraint inference Constrained Markov decision process

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Automated verification of weak equivalence within the SMODELS system

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THEORY AND PRACTICE OF LOGIC programming 2007年第6期7卷 697-744页

作者： Janhunen, Tomi Oikarinen, Emilia Aalto Univ Dept Comp Sci & Engn Lab Theoret Comp Sci FIN-02150 Espoo Finland

In answer set programming (ASP), a problem at hand is solved by (i) writing a logic program whose answer sets correspond to the solutions of the problem, and by (ii) computing the answer sets of the program using an answer set solver as a search engine. Typically, a programmer creates a series of gradually improving logic programs for a particular problem when optimizing program length and execution time on a particular solver. This leads the programmer to a meta-level problem of ensuring that the programs are equivalent, i.e., they give rise to the same answer sets. To case answer set programming at methodological level, we propose a translation-based method for verifying the equivalence of logic programs. The basic idea is to translate logic programs P and Q under consideration into a single logic program EQT(P,Q) whose answer sets (if such exist) yield counter-examples to the equivalence of P and Q. The method is developed here in a slightly more general setting by taking the visibility of atoms properly into account when comparing answer sets. The translation-based approach presented in the paper has been implemented as a translator called LPEQ that enables the verification of weak equivalence within the SMODELS system using the same search engine as for the search of models. Our experiments with LPEQ and SMODELS suggest that establishing the equivalence of logic programs in this way is in certain cases much faster than naive cross-checking of answer sets.

关键词： answer set programming weak equivalence programming methodology program optimization

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Automated legal reasoning with discretion to act using s(LAW)

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ARTIFICIAL INTELLIGENCE AND LAW 2024年第4期32卷 1141-1164页

作者： Arias, Joaquin Moreno-Rebato, Mar Rodriguez-Garcia, Jose A. Ossowski, Sascha Univ Rey Juan Carlos CETINIA Madrid 28933 Spain

Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic programming, specially answer set programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling discretionality to act and other vague concepts such as ambiguity cannot be expressed in top-down execution models based on Prolog, and in bottom-up execution models based on ASP the justifications are incomplete and/or not scalable. We propose to use s(CASP), a top-down execution model for predicate ASP, to model vague concepts following a set of patterns. We have implemented a framework, called s(LAW), to model, reason, and justify the applicable legislation and validate it by translating (and benchmarking) a representative use case, the criteria for the admission of students in the "Comunidad de Madrid".

关键词： answer set programming Goal-directed Ambiguity Administrative discretion

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Random logic programs: Linear model

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THEORY AND PRACTICE OF LOGIC programming 2015年第6期15卷 818-853页

作者： Wang, Kewen Wen, Lian Mu, Kedian Griffith Univ Sch Informat & Commun Technol Nathan Qld 4111 Australia Peking Univ Sch Math Sci Beijing Peoples R China

This paper proposes a model, the linear model, for randomly generating logic programs with low density of rules and investigates statistical properties of such random logic programs. It is mathematically shown that the average number of answer sets for a random program converges to a constant when the number of atoms approaches infinity. Several experimental results are also reported, which justify the suitability of the linear model. It is also experimentally shown that, under this model, the size distribution of answer sets for random programs tends to a normal distribution when the number of atoms is sufficiently large.

关键词： answer set programming random logic programs

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