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LazyBum: Decision Tree Learning Using Lazy Propositionalization 1

29th international conference on inductive logic programming

作者： Schouterden, Jonas Davis, Jesse Blockeel, Hendrik Katholieke Univ Leuven Dept Comp Sci Celestijnenlaan 200ABox 2402 B-3001 Leuven Belgium

ISBN: (数字)9783030492106

ISBN: (纸本)9783030492090;9783030492106

Propositionalization is the process of summarizing relational data into a tabular (attribute-value) format. the resulting table can next be used by any propositional learner. this approach makes it possible to apply a wide variety of learning methods to relational data. However, the transformation from relational to propositional format is generally not lossless: different relational structures may be mapped onto the same feature vector. At the same time, features may be introduced that are not needed for the learning task at hand. In general, it is hard to define a feature space that contains all and only those features that are needed for the learning task. this paper presents LazyBum, a system that can be considered a lazy version of the recently proposed OneBM method for propositionalization. LazyBum interleaves OneBM's feature construction method with a decision tree learner. this learner both uses and guides the propositionalization process. It indicates when and where to look for new features. this approach is similar to what has elsewhere been called dynamic propositionalization. In an experimental comparison with the original OneBM and with two other recently proposed propositionalization methods (nFOIL and MODL, which respectively perform dynamic and static propositionalization), LazyBum achieves a comparable accuracy with a lower execution time on most of the datasets.

关键词： LazyBum inductive logic programming Propositionalization

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Business process verification with constraint temporal answer set programming

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thEORY AND PRACTICE OF logic programming 2013年第4-5期13卷 641-655页

作者： Giordano, Laura Martelli, Alberto Spiotta, Matteo Dupre, Daniele theseider Univ Piemonte Orientale DISIT Alessandria Italy Univ Turin Dipartimento Informat I-10124 Turin Italy

the paper provides a framework for the verification of business processes, based on an extension of answer set programming (ASP) with temporal logic and constraints. the framework allows to capture expressive fluent annotations as well as data awareness in a uniform way. It allows for a declarative specification of a business process but also for encoding processes specified in conventional workflow languages. Verification of temporal properties of a business process, including verification of compliance to business rules, is performed by bounded model checking techniques in Answer Set programming, extended with constraint solving for dealing with conditions on numeric data.

关键词： Statistical Data time characteristic Business process management programming Answer Verification Temporal logic Business

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An Efficient Method for Clock Skew Scheduling to reduce Peak Current 29

An Efficient Method for Clock Skew Scheduling to reduce Peak...

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29th international conference on VLSI DESIGN / 15th international conference on Embedded Systems (VLSID)

作者： Vijayakumar, Arunkumar Patil, Vinay C. Kundu, Sandip Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA

ISBN: (纸本)9781467387002

Concurrent switching of flip-flops and logic gates produces a current surge in synchronous circuits resulting in power supply noise and integrity issues. It is well known that peak current caused by simultaneous switching can be reduced by clock skew scheduling. It has been shown that this problem may be formulated as an integer linear programming problem. However, such formulation is computationally expensive for designs with large number of flip-flops. In this work, we propose a fast heuristic method to schedule clock skew for reducing peak current. the proposed method is evaluated on ISCAS-89, ITC99 and synthetic benchmark circuits. Results show that the proposed method finds a near-optimal solution within minutes even for the largest benchmark circuits.

关键词： Clock skew Peak current Integer Linear programming

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Epistemic Specifications with Probabilities 29

Epistemic Specifications with Probabilities

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

作者： Zhang, Shutao Zhang, Zhizheng Southeast Univ Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538638767

this paper develops a probabilistic-epistemic logic program language, PELP, by introducing probabilistic modal operators K-w and PL into LPMLN programs, where w is a sub-interval of [0, 1]. Intuitively, a probabilistic epistemic literal K(w)e denotes that e is known with a probability in w, and a probabilistic comparing literal PL(e(1), e(2)) denotes it is known that the probability of e(1) is less than the one of e(2). the semantics of the new language is based on the semantics of LPMLN and epistemic specifications. In this paper, we analyze the relationship between PELP and some other epistemic logic programming languages. We also propose an algorithm for solving PELP programs, and then investigate the application of PELP for modeling and solving the Monty Hall problem and a conformant planning problem with a threshold.

关键词： Epistemic logic Program Probabilistic logic Program Nonmontonic Reasoning Probabilistic Reasoning Conformant Probabilistic Planning

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Failure tabled constraint logic programming by interpolation

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thEORY AND PRACTICE OF logic programming 2013年第4-5期13卷 593-607页

作者： Gange, Graeme Navas, Jorge A. Schachte, Peter Sondergaard, Harald Stuckey, Peter J. Univ Melbourne Dept Comp & Informat Syst Melbourne Vic 3010 Australia

We present a new execution strategy for constraint logic programs called Failure Tabled CLP. Similarly to Tabled CLP our strategy records certain derivations in order to prune further derivations. However, our method only learns from failed derivations. this allows us to compute interpolants rather than constraint projection for generation of reuse conditions. As a result, our technique can be used where projection is too expensive or does not exist. Our experiments indicate that Failure Tabling can speed up the execution of programs with many redundant failed derivations as well as achieve termination in the presence of infinite executions.

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Stable Model Counting and Its Application in Probabilistic logic programming 29

Stable Model Counting and Its Application in Probabilistic L...

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29th Association-for-the-Advancement-of-Artificial-Intelligence (AAAI) conference on Artificial Intelligence

作者： Aziz, Rehan Abdul Chu, Geoffrey Muise, Christian Stuckey, Peter Univ Melbourne Natl ICT Australia Victoria Lab Dept Comp & Informat Syst Melbourne Vic Australia

ISBN: (纸本)9781577357032

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given queries being true provided a set of mutually independent random variables, a model (a logic program) and some evidence. the core of solving this inference task involves translating the logic program to a propositional theory and using a model counter. In this paper, we show that for some problems that involve inductive definitions like reachability in a graph, the translation of logic programs to SAT can be expensive for the purpose of solving inference tasks. For such problems, direct implementation of stable model semantics allows for more efficient solving. We present two implementation techniques, based on unfounded set detection, that extend a propositional model counter to a stable model counter. Our experiments show that for particular problems, our approach can outperform a state-of-the-art probabilistic logic programming solver by several orders of magnitude in terms of running time and space requirements, and can solve instances of significantly larger sizes on which the current solver runs out of time or memory.

关键词： Semantics

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the Prolog Debugger and Declarative programming 29th

The Prolog Debugger and Declarative Programming

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29th international conference on logic-Based Program Synthesis and Transformation (LOPSTR)

作者： Drabent, Wlodzimierz Polish Acad Sci Inst Comp Sci Warsaw Poland Linkoping Univ IDA Linkoping Sweden

ISBN: (纸本)9783030452599;9783030452605

logic programming is a declarative programming paradigm. programming language Prolog makes logic programming possible, at least to a substantial extent. However the Prolog debugger works solely in terms of the operational semantics. So it is incompatible with declarative programming. this report discusses this issue and tries to find how the debugger may be used from the declarative point of view. the results are rather not encouraging. Also, the box model of Byrd, used by the debugger, is explained in terms of SLD-resolution.

关键词： Declarative diagnosis/Algorithmic debugging Prolog Declarative programming Program correctness Program completeness

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Learning large logic programs by going beyond entailment 29

Learning large logic programs by going beyond entailment

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29th international Joint conference on Artificial Intelligence, IJCAI 2020

作者： Cropper, Andrew Dumancic, Sebastijan University of Oxford United Kingdom KU Leuven Belgium

ISBN: (纸本)9780999241165

A major challenge in inductive logic programming (ILP) is learning large programs. We argue that a key limitation of existing systems is that they use entailment to guide the hypothesis search. this approach is limited because entailment is a binary decision: a hypothesis either entails an example or does not, and there is no intermediate position. To address this limitation, we go beyond entailment and use example-dependent loss functions to guide the search, where a hypothesis can partially cover an example. We implement our idea in Brute, a new ILP system which uses best-first search, guided by an example-dependent loss function, to incrementally build programs. Our experiments on three diverse program synthesis domains (robot planning, string transformations, and ASCII art), show that Brute can substantially outperform existing ILP systems, both in terms of predictive accuracies and learning times, and can learn programs 20 times larger than state-of-the-art systems. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： inductive logic programming (ILP)

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Language fuzzing using constraint logic programming 14

Language fuzzing using constraint logic programming

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29th ACM/IEEE international conference on Automated Software Engineering, ASE 2014

作者： Dewey, Kyle Roesch, Jared Hardekopf, Ben University of California Santa Barbara United States

ISBN: (纸本)9781450330138

Fuzz testing builds confidence in compilers and interpreters. It is desirable for fuzzers to allow targeted generation of programs that showcase specific language features and behaviors. However, the predominant program generation technique used by most language fuzzers, stochastic context-free grammars, does not have this property. We propose the use of constraint logic programming (CLP) for program generation. Using CLP, testers can write declarative predicates specifying interesting programs, including syntactic features and semantic behaviors. CLP subsumes and generalizes the stochastic grammar approach. © 2014 ACM.

关键词： Semantics

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the jobs puzzle: Taking on the challenge via controlled natural language processing

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thEORY AND PRACTICE OF logic programming 2013年第4-5期13卷 487-501页

作者： Schwitter, Rolf Macquarie Univ Dept Comp Sydney NSW 2109 Australia

In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answer set program and be processed by a state-of-the-art answer set solver to find the solutions to the puzzle.

关键词： Controlled natural language knowledge representation answer set programming

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