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What Makes Propositional Abduction Tractable

机译:是什么使命题绑架变得可行

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Abduction is a fundamental form of nonmonotonic reasoning that aims at finding explanations for observed manifestations. This process underlies many applications, from car configuration to medical diagnosis. We study here the computational complexity of deciding whether an explanation exists in the case when the application domain is described by a propositional knowledge base. Building on previous results, we classify the complexity for local restrictions on the knowledge base and under various restrictions on hypotheses and manifestations. In comparison to the many previous studies on the complexity of abduction we are able to give a much more detailed picture for the complexity of the basic problem of deciding the existence of an explanation. It turns out that depending on the restrictions, the problem in this framework is always polynomial-time solvable, NP-complete, coNP-complete,rnor Σ_2~P complete.rnBased on these results, we give an a posteriori justification of what makes propositional abduction hard even for some classes of knowledge bases which allow for efficient satisfiability testing and deduction. This justification is very simple and intuitive, but it reveals that no nontrivial class of abduction problems is tractable. Indeed, tractability essentially requires that the language for knowledge bases is unable to express both causal links and conflicts between hypotheses. This generalizes a similar observation by Bylander et al. for set-covering abduction.
机译:绑架是非单调推理的基本形式,旨在为观察到的表现找到解释。这个过程是许多应用的基础,从汽车配置到医疗诊断。我们在这里研究在命题知识库描述应用程序域的情况下确定是否存在解释的计算复杂性。基于先前的结果,我们将知识库的局部限制以及假设和表现形式的各种限制归类为复杂性。与以前关于绑架的复杂性的许多研究相比,我们能够对决定解释是否存在的基本问题的复杂性给出更为详尽的描述。事实证明,根据这些限制,此框架中的问题始终是多项式时间可解的,NP完全的,coNP完全的,或Σ_2〜P完全的。即使对于某些类别的知识库也很难进行绑架,这些知识库可以进行有效的满意度测试和推断。这种辩解非常简单和直观,但它表明没有任何平凡的绑架问题是可以解决的。确实,易处理性本质上要求知识库的语言既不能表达因果关系,也不能表达假设之间的冲突。这概括了Bylander等人的类似观察。进行绑架绑架。

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