25,040 research outputs found

    The logic of p-values

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    Wagenmakers et al. addressed the illogic use of p-values in 'Psychological Science under Scrutiny'. While historical criticisms mostly deal with the illogical nature of null hypothesis significance testing (NHST), Wagenmakers et al. generalize such argumentation to the p-value itself. Unfortunately, Wagenmakers et al. misinterpret the formal logic basis of tests of significance (and, by extension, of tests of acceptance). This article highlights three instances where such logical interpretation fails and provides plausible corrections and further clarification

    Introduction to the 26th International Conference on Logic Programming Special Issue

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    This is the preface to the 26th International Conference on Logic Programming Special IssueComment: 6 page

    An anytime deduction heuristic for first order probabilistic logic

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    This thesis describes an anytime deduction heuristic to address the decision and optimization form of the First Order Probabilistic Logic problem which was revived by Nilsson in 1986. Reasoning under uncertainty is always an important issue for AI applications, e.g., expert systems, automated theorem-provers, etc. Among the proposed models and methods for dealing with uncertainty, some as, e.g., Nilsson's ones, are based on logic and probability. Nilsson revisited the early works of Boole (1854) and Hailperin (1976) and reformulated them in an AI framework. The decision form of the probabilistic logic problem, also known as PSAT, consists of finding, given a set of logical sentences together with their probability value to be true, whether the set of sentences and their probability value is consistent. In the optimization form, assuming that a system of probabilistic formulas is already consistent, the problem is: Given an additional sentence, find the tightest possible probability bounds such that the overall system remains consistent with that additional sentence. Solution schemes, both heuristic and exact, have been proposed within the propositional framework. Even though first order logic is more expressive than the propositional one, more works have been published in the propositional framework. The main objective of this thesis is to propose a solution scheme based on a heuristic approach, i.e., an anytime deduction technique, for the decision and optimization form of first order probabilistic logic problem. Jaumard et al. [33] proposed an anytime deduction algorithm for the propositional probabilistic logic which we extended to the first order context

    Quantum teleportation and Grover's algorithm without the wavefunction

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    In the same way as the quantum no-cloning theorem and quantum key distribution in two preceding papers, entanglement-assisted quantum teleportation and Grover's search algorithm are generalized by transferring them to an abstract setting, including usual quantum mechanics as a special case. This again shows that a much more general and abstract access to these quantum mechanical features is possible than commonly thought. A non-classical extension of conditional probability and, particularly, a very special type of state-independent conditional probability are used instead of Hilbert spaces and wavefunctions.Comment: 21 pages, including annex, important typo in annex corrected in v2, Found Phys (2017
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