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Absolute Versus Probabilistic Classification in a Logical Setting

机译:逻辑设置中的绝对与概率分类

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Given a set W of logical structures, or possible worlds, a set D of logical formulas, or possible data, and a logical formula Φ, we consider the classification problem of determining in the limit and almost always correctly whether a possible world M satisfies Φ, from a complete enumeration of the possible data that are true in M. One interpretation of almost always correctly is that the classification might be wrong on a set of possible worlds of measure 0, w.r.t. some natural probability distribution over the set of possible worlds. Another interpretation is that the classifier is only required to classify a set W′ of possible worlds of measure 1, without having to produce any claim in the limit on the truth of Φ in the members of the complement of W′ in W. We compare these notions with absolute classification of W w.r.t. a formula that is almost always equivalent to Φ in W, hence investigate whether the set of possible worlds on which the classification is correct is definable. Finally, in the spirit of the kind of computations considered in Logic programming, we address the issue of computing almost correctly in the limit witnesses to leading existentially quantified variables in existential formulas.
机译:给定逻辑结构的集合W或可能的世界,逻辑公式的集合D,或可能的数据,以及逻辑公式φ,我们考虑确定限制的分类问题,几乎总是正确地正确地正确地满足φ从M的完整枚举完整枚举。几乎总是正确的一个解释是,在一组可能的度量世界中,分类可能是错误的0,WRT一些可能的世界的自然概率分布。另一个解释是,分类器仅需要对可能的度量世界的集合W'进行分类,而不必在W“中的成员中的φ中φ的真实性中的任何声明中。我们比较这些概念绝对分类W WRT几乎总是相当于W中的公式,因此研究了分类是否正确的可能世界中是否可定义。最后,本着逻辑编程中考虑的计算的精神,我们在极限证人中解决了在存在式公式中领先存在量化的变量的极限目击中的计算问题。

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