The 30th edition of the International Conference of logicprogramming took place in Vienna in July 2014 at the Vienna Summer of logic - the largest scientific conference in the history of logic. Following the initiati...
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The 30th edition of the International Conference of logicprogramming took place in Vienna in July 2014 at the Vienna Summer of logic - the largest scientific conference in the history of logic. Following the initiative in 2010 taken by the Association for logicprogramming and Cambridge University Press, the full papers accepted for the International Conference on logicprogramming again appear as a special issue of theory and practice of logic programming (TPLP) - the 30th International Conference on logicprogramming Special Issue. Papers describing original, previously unpublished research and not simultaneously submitted for publication elsewhere were solicited in all areas of logicprogramming including but not restricted to: theory: Semantic Foundations, Formalisms, Non- monotonic Reasoning, Knowledge Representation; Implementation: Compilation, Memory Management, Virtual Machines, Parallelism; Environments: Program Analysis, Transformation, Validation, Verification, Debugging, Profiling, Testing; Language Issues: Concurrency, Objects, Coordination, Mobility, Higher Order, Types, Modes, Assertions, programming Techniques; Related Paradigms: Abductive logicprogramming, Inductive logicprogramming, Constraint logicprogramming, Answer-Set programming; Applications: Databases, Data Integration and Federation, Software Engineering, Natural Language Processing, Web and Semantic Web, Agents, Artificial Intelligence, Bioinformatics.
In response to the so-called software crisis' of the late 1960s, many approaches were proposed to turn (parts of) software engineering and programming into more systematic disciplines, to turn an art into a scienc...
In response to the so-called software crisis' of the late 1960s, many approaches were proposed to turn (parts of) software engineering and programming into more systematic disciplines, to turn an art into a science. This paper studies one popular example often used in these proposals, the computation of a list of primes, to discuss some salient features of the proposed programming paradigms. It also looks at the actual implementation in the early 1970s of the prime program on a time-sharing system (MULTICS) and on a complex scientific computer (ILLIAC IV). Confronting theory with practice uncovers what the programming paradigms fail to grasp: the interaction with the user and the interaction with the machine.
Dependence clusters are (maximal) groups of source code entities that each depend on the other according to some dependence relation. Such clusters are generally seen as detrimental to many software engineering activi...
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We study the framework of abductive logicprogramming extended with integrity constraints. For this framework, we introduce a new measure of the simplicity of an explanation based on its degree of arbitrariness: the m...
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We study the framework of abductive logicprogramming extended with integrity constraints. For this framework, we introduce a new measure of the simplicity of an explanation based on its degree of arbitrariness: the more arbitrary the explanation, the less appealing it is, with explanations having no arbitrariness - they are called constrained - being the preferred ones. In the paper, we study basic properties of constrained explanations. For the case when programs in abductive theories are stratified we establish results providing a detailed picture of the complexity of the problem to decide whether constrained explanations exist.
Query answering in Answer Set programming (ASP) is usually solved by computing (a subset of) the cautious consequences of a logic program. This task is computationally very hard, and there are programs for which compu...
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Query answering in Answer Set programming (ASP) is usually solved by computing (a subset of) the cautious consequences of a logic program. This task is computationally very hard, and there are programs for which computing cautious consequences is not viable in reasonable time. However, current ASP solvers produce the (whole) set of cautious consequences only at the end of their computation. This paper reports on strategies for computing cautious consequences, also introducing anytime algorithms able to produce sound answers during the computation.
To improve performance, modern multiprocessors and programming languages typically implement relaxed memory models that do not require all processors/threads to observe memory operations in the same order. To relieve ...
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Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the ...
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Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the number of instances. Even if various authors have underlined its importance for probabilistic logicprogramming (PLP), lifted inference has been applied up to now only to relational languages outside of logicprogramming. In this paper we adapt Generalized Counting First Order Variable Elimination (GC-FOVE) to the problem of computing the probability of queries to probabilistic logic programs under the distribution semantics. In particular, we extend the Prolog Factor Language (PFL) to include two new types of factors that are needed for representing ProbLog programs. These factors take into account the existing causal independence relationships among random variables and are managed by the extension to variable elimination proposed by Zhang and Poole for dealing with convergent variables and heterogeneous factors. Two new operators are added to GC-FOVE for treating heterogeneous factors. The resulting algorithm, called LP2 for Lifted Probabilistic logicprogramming, has been implemented by modifying the PFL implementation of GC-FOVE and tested on three benchmarks for lifted inference. A comparison with PITA and ProbLog2 shows the potential of the approach.
Datatypes and codatatypes are useful for specifying and reasoning about (possibly infinite) computational processes. The Isabelle/HOL proof assistant has recently been extended with a definitional package that support...
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The semantics of logic programs was originally described in terms of two-valued logic. Soon, however, it was realised that three-valued logic had some natural advantages, as it provides distinct values not only for tr...
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The semantics of logic programs was originally described in terms of two-valued logic. Soon, however, it was realised that three-valued logic had some natural advantages, as it provides distinct values not only for truth and falsehood but also for "undefined". The three-valued semantics proposed by Fitting (Fitting, M. 1985. A Kripke-Kleene semantics for logic programs. Journal of logicprogramming 2, 4, 295-312) and Kunen (Kunen, K. 1987. Negation in logicprogramming. Journal of logicprogramming 4, 4, 289-308) are closely related to what is computed by a logic program, the third truth value being associated with non-termination. A different three-valued semantics, proposed by Naish, shared much with those of Fitting and Kunen but incorporated allowances for programmer intent, the third truth value being associated with underspecification. Naish used an (apparently) novel "arrow" operator to relate the intended meaning of left and right sides of predicate definitions. In this paper we suggest that the additional truth values of Fitting/Kunen and Naish are best viewed as duals. We use Belnap's four-valued logic (Belnap, N. D. 1977. A useful four-valued logic. In Modern Uses of Multiple-Valued logic, J. M. Dunn and G. Epstein, Eds. D. Reidel, Dordrecht, Netherlands, 8-37), also used elsewhere by Fitting, to unify the two three-valued approaches. The truth values are arranged in a bilattice, which supports the classical ordering on truth values as well as the "information ordering". We note that the "arrow" operator of Naish (and our four-valued extension) is essentially the information ordering, whereas the classical arrow denotes the truth ordering. This allows us to shed new light on many aspects of logicprogramming, including program analysis, type and mode systems, declarative debugging and the relationships between specifications and programs, and successive execution states of a program.
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