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A polynomial-time fragment of epistemic probabilistic argumentation

机译:认知概率论证的多项式时间片段

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Probabilistic argumentation allows reasoning about argumentation problems in a way that is well-founded by probability theory. However, in practice, this approach can be severely limited by the fact that probabilities are defined by adding an exponential number of terms. We show that this exponential blowup can be avoided in an interesting fragment of epistemic probabilistic argumentation and that some computational problems that have been considered intractable can be solved in polynomial time. We give efficient convex programming formulations for these problems and explore how far our fragment can be extended without losing tractability. (C) 2019 Elsevier Inc. All rights reserved.
机译:概率论证允许以概率论有充分根据的方式对论证问题进行推理。但是,实际上,这种方法可能会受到以下事实的严重限制:概率是通过增加指数项来定义的。我们表明,可以在认知概率论证的有趣片段中避免这种指数爆炸,并且可以在多项式时间内解决一些被认为难以解决的计算问题。我们为这些问题提供了有效的凸规划公式,并探讨了在不失去可处理性的情况下可以将片段扩展到多远。 (C)2019 Elsevier Inc.保留所有权利。

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