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Algorithmic complexity of recursive and inductive algorithms

机译:递归和归纳算法的算法复杂度

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摘要

The main goal of this paper is to compare recursive algorithms such as Turing machines with such super-recursive algorithms as inductive Turing machines. This comparison is made in a general setting of dual complexity measures such as Kolmogorov or algorithmic complexity. To make adequate comparison, we reconsider the standard axiomatic approach to complexity of algorithms. The new approach allows us to achieve a more adequate representation of static system complexity in the axiomatic context. It is demonstrated that for solving many problems inductive Turing machines have much lower complexity than Turing machines and other recursive algorithms. Thus, inductive Turing machines are not only more powerful, but also more efficient than Turing machines.
机译:本文的主要目的是将递归算法(如图灵机)与超递归算法(如归纳图灵机)进行比较。这种比较是在双重复杂性度量(例如Kolmogorov或算法复杂性)的一般设置下进行的。为了进行充分的比较,我们重新考虑了针对算法复杂性的标准公理方法。新方法使我们能够在公理环境中更充分地表示静态系统的复杂性。事实证明,对于解决许多问题,归纳图灵机比图灵机和其他递归算法具有更低的复杂度。因此,感应图灵机不仅比图灵机更强大,而且效率更高。

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