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arXiv 2102.10416cs.FL
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最简单的非正则确定上下文无关语言

Simplest Non-Regular Deterministic Context-Free Language

Petr Jancar, Jiri Sima

摘要:

我们引入了一个新的概念,C-简单的问题,一类C的决策问题(即语言),w.r.t.一个特别的减少。一个问题是C-简单的,如果它可以减少到C中的每个问题。这可以被看作是一个概念对应的C-困难的问题,所有的问题在C中减少。我们的具体例子是一类非正则确定性上下文无关语言(DCFL '),用Mealy机器(证明是前序)进行真值表约简。主要的技术结果是证明了DCFL的语言$L=\{0^n1^n; n\geq 1\}$是DCFL“-简单的,因此可以被看作是类DCFL”中最简单的问题。该结果已经为模拟神经元层次结构第一级的神经网络1 ANN的计算模型提供了应用。该模型被证明不识别$L$,通过使用一个专门的技术参数,很难推广到其他语言的DCFL '。根据$L$是DCFL '-简单的结果,证明了$L$是DCFL'-简单的。通过对1ANN所能实现的约简的分析,我们立即得出1ANN不能接受DCFL中的任何语言。因此,似乎值得探讨的是,在适当的约简下,在其他C类中寻找C-简单问题是否可以提供有效的工具,将已知的单个问题的下界结果扩展到整个问题类。

英文摘要:

We introduce a new notion of C-simple problems for a class C of decision problems (i.e. languages), w.r.t. a particular reduction. A problem is C-simple if it can be reduced to each problem in C. This can be viewed as a conceptual counterpart to C-hard problems to which all problems in C reduce. Our concrete example is the class of non-regular deterministic context-free languages (DCFL'), with a truth-table reduction by Mealy machines (which proves to be a preorder). The main technical result is a proof that the DCFL' language $L=\{0^n1^n; n\geq 1\}$ is DCFL'-simple, which can thus be viewed as the simplest problem in the class DCFL'. This result has already provided an application, to the computational model of neural networks 1ANN at the first level of analog neuron hierarchy. This model was proven not to recognize $L$, by using a specialized technical argument that can hardly be generalized to other languages in DCFL'. By the result that $L$ is DCFL'-simple, w.r.t. the reduction that can be implemented by 1ANN, we immediately obtain that 1ANN cannot accept any language in DCFL'. It thus seems worthwhile to explore if looking for C-simple problems in other classes C under suitable reductions could provide effective tools for expanding the lower-bound results known for single problems to the whole classes of problems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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