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Unifying Probability with Nondeterminism

机译:用不确定性统一概率

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Early support for reasoning about probabilistic system behaviour replaced nondeterminism with probabilism. Only relatively recently have formalisms been studied that combine the two, and hence facilitate reasoning about probabilistic systems at levels of abstraction more general than code. Such studies have revealed an unsuspected subtlety in the interaction between nondeterministic and probabilistic choices that can be summarised: the demon resolving the nondeterministic choice has memory of previous state changes, whilst the probabilistic choice is made spontaneously. As a result, assignments to distinct variables need no longer commute. This paper introduces a model with explicit control of the length of the demon's memory. It does so by expanding the standard (initial-final) state view of computation to incorporate a third state, the 'original' state which checkpoints the most recent nondeterministic choice. That enables a nondeterministic choice to be made on the basis of only certain past probabilistic choices and so facilitates independent nondeterministic combinations to be chosen against just those. Sound laws are presented and used to analyse first an example in which no new behaviour should result, and second one that lies beyond the scope of traditional models.
机译:对概率系统行为推理的早期支持用概率论代替了不确定性。直到最近才研究了将两者结合起来的形式主义,因此可以在比代码更笼统的抽象级别上促进概率系统的推理。这样的研究表明,不确定性选择和概率选择之间的相互作用具有不可预见的微妙之处,可以总结如下:解决不确定性选择的恶魔具有先前状态变化的记忆,而概率选择是自发的。结果,对不同变量的分配不再需要上下班。本文介绍了一个模型,其中明确控制了恶魔的记忆长度。它通过扩展计算的标准(初始-最终)状态视图来合并第三种状态,即“原始”状态,该状态检查点确定了最新的不确定性选择。这使得能够仅基于过去的某些概率选择来做出不确定性选择,并且因此便于针对那些不确定性选择独立的不确定性组合。提出合理的定律并将其用于分析一个示例,在该示例中不应导致任何新行为,其次则超出了传统模型的范围。

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