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29th Annual IEEE international conference on Tools with Artificial Intelligence (ICTAI)

作者： Leger, Hippolyte Bouthinon, Dominique Lebbah, Mustapha Azzag, Hanene Univ Paris 13 LIPN UMR CNRS 7030 99 Ave Jean Baptiste Clement F-93430 Villetaneuse France

ISBN: (纸本)9781538638767

the theta-subsumption test is known to be a bottleneck in inductive logic programming. the state-of-the-art learning systems in this field are hardly scalable. Last year, we have created a distributed theta-subsumption process based on an Actor Model, with the aim of being able to decide subsumption on very large clauses. this model was correct and complete, but was also very slow. this is why we introduce ANTS (Actor Network based theta-Subsumption), a new model also based on an actor network, which is significantly faster than the previous one.

关键词： theta-subsumption inductive logic programming actor model distributed computing Akka

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Compiling Input* FO(.) inductive definitions into tabled prolog rules for IDP3

<i>Compiling Input</i>* FO(.) <i>inductive definitions into ...

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29th international conference on logic programming ICLP

作者： Jansen, Joachim Jorissen, Albert Janssens, Gerda Katholieke Univ Leuven Dept Comp Sci Louvain Belgium

FO(.)(IDP3) extends first-order logic with inductive definitions, partial functions, types and aggregates. Its model generator IDP3 first grounds the theory and then uses search to find the models. the grounder uses Lifted Unit Propagation (LUP) to reduce the size of the groundings of problem specifications in IDP3. LUP is in general very effective, but performs poorly on definitions of predicates whose two-valued interpretation can be computed from data in the input structure. To solve this problem, a preprocessing step is introduced that converts such definitions to Prolog code and uses XSB Prolog to compute their interpretation. the interpretation of these predicates is then added to the input structure, their definitions are removed from the theory and further processing is done by the standard IDP3 system. Experimental results show the effectiveness of our method.

关键词： program transformation FO(.) logic programming tabling knowledge base systems IDP system declarative modeling

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Towards an ILP Application in Machine Ethics 1

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29th international conference on inductive logic programming

作者： Dyoub, Abeer Costantini, Stefania Lisi, Francesca A. Univ Aquila Dipartimento Ingn & Sci Informaz & Matemat Laquila Italy Univ Bari Aldo Moro Dipartimento Informat Bari Italy Univ Bari Aldo Moro Ctr Interdipartimentale Log & Applicaz Bari Italy

ISBN: (数字)9783030492106

ISBN: (纸本)9783030492090;9783030492106

Machine Ethics is a newly emerging interdisciplinary field which is concerned with adding an ethical dimension to Artificial Intelligent (AI) agents. In this paper we address the problem of representing and acquiring rules of codes of ethics in the online customer service domain. the proposed solution approach relies on the non-monotonic features of Answer Set programming (ASP) and applies ILP. the approach is illustrated by means of examples taken from the preliminary tests conducted with a couple of state-of-the-art ILP algorithms for learning ASP rules.

关键词： Answer Set programming Machine Ethics ILP Applications

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Turning 30: New ideas in inductive logic programming 29

Turning 30: New ideas in inductive logic programming

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29th international Joint conference on Artificial Intelligence, IJCAI 2020

作者： Cropper, Andrew Dumancic, Sebastijan Muggleton, Stephen H. University of Oxford United Kingdom KU Leuven Belgium Imperial College London United Kingdom

ISBN: (纸本)9780999241165

Common criticisms of state-of-the-art machine learning include poor generalisation, a lack of interpretability, and a need for large amounts of training data. We survey recent work in inductive logic programming (ILP), a form of machine learning that induces logic programs from data, which has shown promise at addressing these limitations. We focus on new methods for learning recursive programs that generalise from few examples, a shift from using hand-crafted background knowledge to learning background knowledge, and the use of different technologies, notably answer set programming and neural networks. As ILP approaches 30, we also discuss directions for future research. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Machine learning

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Learning logic Programs from Noisy State Transition Data 1

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29th international conference on inductive logic programming

作者： Phua, Yin Jun Inoue, Katsumi SOKENDAI Grad Univ Adv Studies Dept Informat Tokyo Japan Natl Inst Informat Tokyo Japan

ISBN: (数字)9783030492106

ISBN: (纸本)9783030492090;9783030492106

Real world data are often noisy and fuzzy. Most traditional logical machine learning methods require the data to be first discretized dor pre-processed before being able to produce useful output. Such short-coming often limits their application to real world data. On the other hand, neural networks are generally known to be robust against noisy data. However, a fully trained neural network does not provide easily understandable rules that can be used to understand the underlying model. In this paper, we propose a Differentiable Learning from Interpretation Transition (d-LFIT) algorithm, that can simultaneously output logic programs fully explaining the state transitions, and also learn from data containing noise and error.

关键词： Neural network Machine learning Interpretability LFIT

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Rapid Restart Hill Climbing for Learning Description logic Concepts 1

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29th international conference on inductive logic programming

作者： Hua, Yingbing Hein, Bjoern Karlsruhe Inst Technol D-76131 Karlsruhe Germany Karlsruhe Univ Appl Sci D-76131 Karlsruhe Germany

ISBN: (数字)9783030492106

ISBN: (纸本)9783030492090;9783030492106

Recent advances in learning description logic (DL) concepts usually employ a downward refinement operator for space traversing and hypotheses construction. However, theoretical research proved that ideal refinement operator does not exist for expressive DLs, including the language ALC. the state-of-the-art learning framework DL-Learner suggests to use a complete and proper refinement operator and to handle infiniteness algorithmically. For example, the CELOE algorithm follows an iterative widening approach to build a search tree of concept hypotheses. To select a tree node for expansion, CELOE adopts a simple greedy strategy that neglects the structure of the search tree. In this paper, we present the Rapid Restart Hill Climbing (RRHC) algorithm that selects a node for expansion by traversing the search tree in a hill climbing manner and rapidly restarts with one-step backtracking after each expansion. We provide an implementation of RRHC in the DL-Learner framework and compare its performance with CELOE using standard benchmarks.

关键词： Concept learning Description logics Hill Climbing

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Fuzzy answer sets approximations

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thEORY AND PRACTICE OF logic programming 2013年第4-5期13卷 753-767页

作者： Alviano, Mario Penaloza, Rafael Univ Calabria Dept Math & Comp Sci I-87036 Arcavacata Di Rende CS Italy Tech Univ Dresden D-01062 Dresden Germany Ctr Adv Elect Dresden Dresden Germany

Fuzzy answer set programming (FASP) is a recent formalism for knowledge representation that enriches the declarativity of answer set programming by allowing propositions to be graded. To now, no implementations of FASP solvers are available and all current proposals are based on compilations of logic programs into different paradigms, like mixed integer programs or bilevel programs. these approaches introduce many auxiliary variables which might affect the performance of a solver negatively. To limit this downside, operators for approximating fuzzy answer sets can be introduced: Given a FASP program, these operators compute lower and upper bounds for all atoms in the program such that all answer sets are between these bounds. this paper analyzes several operators of this kind which are based on linear programming, fuzzy unfounded sets and source pointers. Furthermore, the paper reports on a prototypical implementation, also describing strategies for avoiding computations of these operators when they are guaranteed to not improve current bounds. the operators and their implementation can be used to obtain more constrained mixed integer or bilevel programs, or even for providing a basis for implementing a native FASP solver. Interestingly, the semantics of relevant classes of programs with unique answer sets, like positive programs and programs with stratified negation, can be already computed by the prototype without the need for an external tool.

关键词： fuzzy logic answer set programming search-space pruning operators

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logic programming with function symbols: Checking termination of bottom-up evaluation through program adornments

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thEORY AND PRACTICE OF logic programming 2013年第4-5期13卷 737-752页

作者： Greco, Sergio Molinaro, Cristian Trubitsyna, Irina Univ Calabria DIMES I-87030 Commenda Di Rende Italy

Recent years have witnessed an increasing interest in enhancing answer set solvers by allowing function symbols. Since the introduction of function symbols makes common inference tasks undecidable, research has focused on identifying classes of programs allowing only a restricted use of function symbols while ensuring decidability of common inference tasks. Finitely-ground programs, introduced in Calimeri et al. (2008), are guaranteed to admit a finite number of stable models with each of them of finite size. Stable models of such programs can be computed and thus common inference tasks become decidable. Unfortunately, checking whether a program is finitely-ground is semi-decidable. this has led to several decidable criteria, called termination criteria, providing sufficient conditions for a program to be finitely-ground. this paper presents a new technique that, used in conjunction with current termination criteria, allows us to detect more programs as finitely-ground. Specifically, the proposed technique takes a logic program P and transforms it into an adorned program P-mu with the aim of applying termination criteria to P-mu rather than P. the transformation is sound in that if the adorned program satisfies a certain termination criterion, then the original program is finitely-ground. Importantly, applying termination criteria to adorned programs rather than the original ones strictly enlarges the class of programs recognized as finitely-ground.

关键词： logic programming with function symbols bottom-up evaluation program evaluation termination stable models

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Domain modeling for planning as logic programming 29

Domain modeling for planning as logic programming

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29th international Florida Artificial Intelligence Research Society conference, FLAIRS 2016

作者： Barták, Roman Vodrážka, Jindřich Charles University in Prague Faculty of Mathematics and Physics Malostranské nám. 25 Praha 1118 00 Czech Republic

ISBN: (纸本)9781577357568

Planning as programming is an approach to automated planning, where the planning domain model is expressed as a program in some (declarative) programming language. then the modeler can exploit all features of that language to encode control knowledge important for efficient planning. In this paper we study these features in the logic programming language Pi-cat and its planner module. In particular, we use two planning benchmarks, Nomystery and Childsnack, to compare factored and structured representations of states extended by encodings of control knowledge. © 2016, Association for the Advancement of Artificial Intelligence (***). All rights ***: Research is supported by the Czech Science Foundation under the project P103-15-19877S.

关键词： logic programming

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Evaluating Epistemic logic Programs via Answer Set programming with Quantifiers 1

Evaluating Epistemic Logic Programs via Answer Set Programmi...

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1st international Workshop on HYbrid Models for Coupling Deductive and inductive ReAsoning and the 29th RCRA Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, HYDRA-RCRA 2022

作者： Faber, Wolfgang Morak, Michael University of Klagenfurt Klagenfurt Austria

In this paper we introduce a simple way to evaluate epistemic logic programs by means of answer set programming with quantifiers, a recently proposed extension of answer set programming. the method can easily be adapted for most of the many semantics that were proposed for epistemic logic programs. We evaluate the proposed transformation on existing benchmarks using a recently proposed solver for answer set programming with quantifiers, which relies on QBF solvers. © 2022 Copyright for this paper by its authors.

关键词： Semantics

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