This paper presents a Prolog interface to the MiniSat satisfiability solver. logicprogramming with satisfiability combines the strengths of the two paradigms: logicprogramming for encoding search problems into satis...
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This paper presents a Prolog interface to the MiniSat satisfiability solver. logicprogramming with satisfiability combines the strengths of the two paradigms: logicprogramming for encoding search problems into satisfiability on the one hand and efficient SAT solving on the other. This synergy between these two exposes a programming paradigm that we propose here as a logicprogramming pearl. To illustrate logicprogramming with SAT solving, we give an example Prolog program that solves instances of Partial MAXSAT.
We define a semantics for negation as failure in logicprogramming. Our semantics may be viewed as a cross between the approaches of Clark [5] and Fitting [7]. As does [7], our semantics corresponds well with real PRO...
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We define a semantics for negation as failure in logicprogramming. Our semantics may be viewed as a cross between the approaches of Clark [5] and Fitting [7]. As does [7], our semantics corresponds well with real PROLOG in the standard examples used in the literature to illustrate problems with [5]. Also, PROLOG and the common variants of it are sound but not complete for our semantics. Unlike [7], our semantics is constructive, in that the set of supported queries is recursively enumerable. Thus, a complete interpreter exists in theory, although we point out that there are serious difficulties in building one that works well in practice.
New generations of distributed systems are opening novel perspectives for logicprogramming (LP): On the one hand, service-oriented architectures represent nowadays the standard approach for distributed systems engine...
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New generations of distributed systems are opening novel perspectives for logicprogramming (LP): On the one hand, service-oriented architectures represent nowadays the standard approach for distributed systems engineering;on the other hand, pervasive systems mandate for situated intelligence. In this paper, we introduce the notion of logicprogramming as a Service (LPaaS) as a means to address the needs of pervasive intelligent systems through logic engines exploited as a distributed service. First, we define the abstract architectural model by re-interpreting classical LP notions in the new context;then we elaborate on the nature of LP interpreted as a service by describing the basic LPaaS interface. Finally, we show how LPaaS works in practice by discussing its implementation in terms of distributed tuProlog engines, accounting for basic issues such as interoperability and configurability.
This paper presents PFLP, a library for probabilistic programming in the functional logicprogramming language Curry. It demonstrates how the concepts of a functional logicprogramming language support the implementat...
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This paper presents PFLP, a library for probabilistic programming in the functional logicprogramming language Curry. It demonstrates how the concepts of a functional logicprogramming language support the implementation of a library for probabilistic programming. In fact, the paradigms of functional logic and probabilistic programming are closely connected. That is, language characteristics from one area exist in the other and vice versa. For example, the concepts of non-deterministic choice and call-time choice as known from functional logicprogramming are related to and coincide with stochastic memoization and probabilistic choice in probabilistic programming, respectively. We will further see that an implementation based on the concepts of functional logicprogramming can have benefits with respect to performance compared to a standard list-based implementation and can even compete with full-blown probabilistic programming languages, which we illustrate by several benchmarks.
In everyday life it happens that a person has to reason out what other people think and how they behave, in order to achieve his goals. In other words, an individual may be required to adapt his behavior by reasoning ...
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In everyday life it happens that a person has to reason out what other people think and how they behave, in order to achieve his goals. In other words, an individual may be required to adapt his behavior by reasoning about the others' mental state. In this paper we focus on a knowledge-representation language derived from logicprogramming which both supports the representation of mental states of individual communities and provides each with the capability of reasoning about others' mental states and acting accordingly. The proposed semantics is shown to be translatable into stable model semantics of logic programs with aggregates.
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 P...
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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 reasoning for such systems of equations. Based on Pearl's calculus, we provide a procedure for processing these counterfactual queries on ProbLog programs, together with a proof of correctness and a full implementation. Using the latter, we provide insights into the influence of different parameters on the scalability of inference. Finally, we also show that our approach is consistent with CP-logic, that is with the causal semantics for logic programs with annotated with disjunctions.
Recent progress in logicprogramming (e.g. the development of the answer set programming (ASP) paradigm) has made it possible to teach it to general undergraduate and even middle/high school students. Given the limite...
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Recent progress in logicprogramming (e.g. the development of the answer set programming (ASP) paradigm) has made it possible to teach it to general undergraduate and even middle/high school students. Given the limited exposure of these students to computer science, the complexity of downloading, installing, and using tools for writing logic programs could be a major barrier for logicprogramming to reach a much wider audience. We developed onlineSPARC, an online ASP environment with a self-contained file system and a simple interface. It allows users to type/edit logic programs and perform several tasks over programs, including asking a query to a program, getting the answer sets of a program, and producing a drawing/animation based on the answer sets of a program.
Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. logic-based approaches are of special interest in CER, since, via Statistical Relationa...
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Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We present a system based on Answer Set programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt online. We compare our ASP-based implementation with a Markov logic-based one and with a number of state-of-the-art batch learning algorithms on CER data sets for activity recognition, maritime surveillance and fleet management. Our results demonstrate the superiority of our novel approach, both in terms of efficiency and predictive performance. This paper is under consideration for publication in theory and practice of logic programming (TPLP).
Constraint logicprogramming (CLP) and Hereditary Harrop formulas (HH) are two well known ways to enhance the expressivity of Horn clauses. In this paper, we present a novel combination of these two approaches. We sho...
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Constraint logicprogramming (CLP) and Hereditary Harrop formulas (HH) are two well known ways to enhance the expressivity of Horn clauses. In this paper, we present a novel combination of these two approaches. We show how to enrich the syntax and proof theory of HH with the help of a given constraint system, in such a way that the key property of HH as a logicprogramming language (namely, the existence of uniform proofs) is preserved. We also present a procedure for goal solving, showing its soundness and completeness for computing answer constraints. As a consequence of this result, we obtain a new strong completeness theorem for CLP that avoids the need to build disjunctions of computed answers, as well as a more abstract formulation of a known completeness theorem for HH.
Constraint Handling Rules (CHR) are our proposal to allow more flexibility and application-oriented customization of constraint systems. CHR are a declarative language extension especially designed for writing user-de...
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Constraint Handling Rules (CHR) are our proposal to allow more flexibility and application-oriented customization of constraint systems. CHR are a declarative language extension especially designed for writing user-defined constraints. CHR are essentially a committed-choice language consisting of multi-headed gurded rules that rewrite constraints into simpler ones until they are solved. In this broad survey we aim at covering all aspects of CHR as they currently present themselves. Going from theory to practice, we will define syntax and semantics for CHR, introduce an important decidable property, confluence, of CHR programs and define a tight integration of CHR with constraint logicprogramming languages. This survey then describes implementations of the language before we review several constraint solvers both traditional and nonstandard ones - written in the CHR language. Finally we introduce two innovative applications that benefited from using CHR. (C) 1998 Elsevier Science Inc. All rights reserved.
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