Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. Recently, the formal link between this research area and satisfiability modulo the...
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We examine the practicality for a user of using Answer Set programming (ASP) for representing logical formalisms. We choose as an example a formalism aiming at capturing causal explanations from causal information. We...
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Sharing, a domain due to D. Jacobs and A. Langen for the analysis of logic programs, derives useful aliasing information. It is well-known that a commonly used core of techniques, such as the standard integration of S...
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ISBN:
(纸本)1581132654
Sharing, a domain due to D. Jacobs and A. Langen for the analysis of logic programs, derives useful aliasing information. It is well-known that a commonly used core of techniques, such as the standard integration of Sharing with freeness and linearity information, can significantly improve the precision of Sharing. However, a number of other proposals for refined domain combinations have been circulating for years. One feature that is common to these proposals is that they do not seem to have undergone a thorough experimental evaluation even with respect to the expected precision gains. In this paper, we discuss and/or experimentally evaluate: helping Sharing with definitely ground variables computed with Pos;the incorporation of explicit structural information into the domain of analysis;more sophisticated ways of integrating Sharing and Pos;the issue of reordering the bindings in the computation of the abstract mgu;an original proposal concerning the addition of a domain recording the set of variables that are deemed to be ground or free;a more refined way of using linearity to improve the analysis;the issue of whether tracking compoundness allows to compute more precise sharing information;and, finally, the recovery of hidden information in the combination of Sharing with the usual domain for freeness.
The data on which a MLP (multi-layer perception) is to be trained to approximate a continuous function may include inputs that are categorical rather than only numeric or quantitative. However an MLP with connection m...
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ISBN:
(纸本)0889864586
The data on which a MLP (multi-layer perception) is to be trained to approximate a continuous function may include inputs that are categorical rather than only numeric or quantitative. However an MLP with connection matrices that multiply input values and sigmoid functions that further transform values represents a continuous mapping in all input variables. A MLP therefore requires that all inputs correspond to numeric, continuously valued variables and represents a continuous function in all input variables. On the other hand a categorical variable produces a discontinuous relationship between an input variable and the output. The way that this problem is often dealt with is to replace the categorical values by numeric ones and treat them as if they were continuously valued. However there is no meaningful correspondence between the continuous quantities generated this way and the original categorical values. An approach examined in this paper is to train a standard feedforward network with the numeric portion of the input only and train another network with the categorical portion of the input to produce a selector vector. The selector vector produced by the second network selects output from the first network.
We present a sound and complete logic for reasoning about SimpleAPL programs. SimpleAPL is a fragment of the agent programming language 3APL designed for the implementation of cognitive agents with beliefs, goals and ...
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When modelling expert knowledge, default negation is very useful, but might lead to there being no stable models. Detecting the exact causes of the incoherence in the logic program manually can become quite cumbersome...
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This paper presents an abstract domain and an abstract unification function for type an al:ysis of logic programs with type definitions. Type information is inferred together with sharing and aliasing information. Ali...
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Realizability interpretations of logics are given by saying what it means for computational objects of some kind to realize, logical formulae. The computational objects in question might be drawn from an untyped unive...
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Realizability interpretations of logics are given by saying what it means for computational objects of some kind to realize, logical formulae. The computational objects in question might be drawn from an untyped universe of computation, such as a partial combinatory algebra, or they might be typed objects such as terms of a PCF-style programming language. In some instances, one can show that a particular untyped realizability interpretation matches a particular typed one, in the sense that they give the same set of realizable formulae. In this case, we have a very good fit indeed between the typed language and the untyped realizability model-we refer to this condition as (constructive) logical full abstraction., We give some examples of this situation for a variety of extensions of PCF. Of particular interest are some models that are logically fully abstract for typed languages including non-functional, features. Our results establish connections between what is computable in various programming languages, and what is true inside various realizability toposes. We consider some examples of logical formulae to illustrate these ideas, in particular their application to exact real-number computability. The present article summarizes the material I presented at the Domains IV workshop, plus a few subsequent developments;it is really an extended abstract for a projected journal paper. No proofs are included in the present version. I am grateful to Martin Escardó for many stimulating discussions, and especially for his input to the material in Sections 4.3 and 5.2. I also thank all the participants in the Domains IV workshop for their interest and encouragement. Andrej Bauer drew my attention to some over-enthusiastic claims involving uniform continuity on my Last Slide. The motivating philosophy behind this work owes much to the influence of Martin Hyland, and to my collaboration with Alex Simpson. This research was funded by the EPSRC Research Grant GR/L89532 "Notions of
To achieve efficient and good performance of logic programs a proposed parallel execution model based on MUSE which was implemented by SICS of Sweden has been developed and implemented. This model is an amalgamation o...
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To achieve efficient and good performance of logic programs a proposed parallel execution model based on MUSE which was implemented by SICS of Sweden has been developed and implemented. This model is an amalgamation of two main types of parallelism: AND-parallelism and OR-parallelism. The implementation of this model is done on a shared memory multiprocessor. Due to this model the logic program can be described by an AND/OR tree. The different branches of this tree are distributed to the available Processing Elements (PEs) during run time. Two scheduling techniques have been developed and implemented. In the first scheduler, The PEs are distributed through the AND/OR tree based on the sequential PROLOG (***-right depth first). The second scheduler is based on the static processing element allocation. Two benchmark programs have been used to assess the performance of this execution model;these are the natural language processing parser and an animal recognition expert system.
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