26,626 research outputs found
Multiconditional Approximate Reasoning with Continuous Piecewise Linear Membership Functions
It is shown that, for some intersection and implication functions, an exact and efficient algorithm exists for the computation of inference results in multiconditional approximate reasoning on domains which are finite intervals of the real numbers, when membership functions are restricted to functions which are continuous and piecewise linear. An implementation of the algorithm is given in the functional programming language Miranda
The Energetic Reasoning Checker Revisited
Energetic Reasoning (ER) is a powerful filtering algorithm for the Cumulative
constraint. Unfortunately, ER is generally too costly to be used in practice.
One reason of its bad behavior is that many intervals are considered as
relevant by the checker of ER, although most of them should be ignored. In this
paper, we provide a sharp characterization that allows to reduce the number of
intervals by a factor seven. Our experiments show that associating this checker
with a Time-Table filtering algorithm leads to promising results.Comment: CP Doctoral Program 2013, Uppsala : Sweden (2013
Statistical relational learning with soft quantifiers
Quantification in statistical relational learning (SRL) is either existential or universal, however humans might be more inclined to express knowledge using soft quantifiers, such as ``most'' and ``a few''. In this paper, we define the syntax and semantics of PSL^Q, a new SRL framework that supports reasoning with soft quantifiers, and present its most probable explanation (MPE) inference algorithm. To the best of our knowledge, PSL^Q is the first SRL framework that combines soft quantifiers with first-order logic rules for modelling uncertain relational data. Our experimental results for link prediction in social trust networks demonstrate that the use of soft quantifiers not only allows for a natural and intuitive formulation of domain knowledge, but also improves the accuracy of inferred results
Formalization of Transform Methods using HOL Light
Transform methods, like Laplace and Fourier, are frequently used for
analyzing the dynamical behaviour of engineering and physical systems, based on
their transfer function, and frequency response or the solutions of their
corresponding differential equations. In this paper, we present an ongoing
project, which focuses on the higher-order logic formalization of transform
methods using HOL Light theorem prover. In particular, we present the
motivation of the formalization, which is followed by the related work. Next,
we present the task completed so far while highlighting some of the challenges
faced during the formalization. Finally, we present a roadmap to achieve our
objectives, the current status and the future goals for this project.Comment: 15 Pages, CICM 201
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