Inductively Computable Hierarchies and Inductive Algorithmic Complexity

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Mark Burgin
Mark Burgin
1 University of California

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Induction is a prevalent cognitive method in science, while inductive computations are popular in many fields of computer and network technology. The most advanced mathematical model of inductive computations and reasoning is an inductive Turing machine, which is natural extension of the most widespread model of computing devices and computations -Turing machine. In comparison with Turing machines, inductive Turing machines represent the next step in the development of computer science providing better models for contemporary computers and computer networks. In this paper (Section 3), we study relations between inductively computable sets, inductively recognizable sets, inductively decidable sets and inductively computable functions. In addition (Section 4), we apply the obtained results to algorithmic information theory demonstrating how inductive Turing machines allow obtaining more information for essentially decreasing complexity in comparison with Turing machines.

13 Cites in Articles

References

  1. Vieri Benci,C Bonanno,Stefano Galatolo,G Menconi,M Virgilio (2002). Dynamical systems and computable information.
  2. A Beros (2013). Learning Theory in the Arithmetical Hierarchy.
  3. M Burgin (1990). Generalized Kolmogorov Complexity and other Dual Complexity Measures.
  4. M Burgin (1999). Super-recursive Algorithms as a Tool for High Performance Computing.
  5. M Burgin (2004). Algorithmic Complexity of Recursive and Inductive Algorithms.
  6. M Burgin (2005). Super-recursive Algorithms.
  7. M Burgin (2006). Algorithmic Control in Concurrent Computations.
  8. M Burgin (2010). Theory of Information: Fundamentality, Diversity and Unification.
  9. M Burgin (2010). Algorithmic Complexity of Computational Problems.
  10. M Burgin (2010). Measuring Power of Algorithms, Computer Programs, and Information Automata.
  11. Mark Burgin,Cristian Calude,Elena Calude (2011). INDUCTIVE COMPLEXITY MEASURES FOR MATHEMATICAL PROBLEMS.
  12. Ulvi Yurtsever (2000). Quantum mechanics and algorithmic randomness.
  13. W Zurek (1990). Algorithmic information content, Church-Turing thesis, physical entropy, and Maxwell's demon.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Mark Burgin. 2016. \u201cInductively Computable Hierarchies and Inductive Algorithmic Complexity\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 16 (GJCST Volume 16 Issue H1): .

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GJCST Volume 16 Issue H1
Pg. 35- 45
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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F.1.3 F.2.2
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v1.2

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March 4, 2016

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English

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Induction is a prevalent cognitive method in science, while inductive computations are popular in many fields of computer and network technology. The most advanced mathematical model of inductive computations and reasoning is an inductive Turing machine, which is natural extension of the most widespread model of computing devices and computations -Turing machine. In comparison with Turing machines, inductive Turing machines represent the next step in the development of computer science providing better models for contemporary computers and computer networks. In this paper (Section 3), we study relations between inductively computable sets, inductively recognizable sets, inductively decidable sets and inductively computable functions. In addition (Section 4), we apply the obtained results to algorithmic information theory demonstrating how inductive Turing machines allow obtaining more information for essentially decreasing complexity in comparison with Turing machines.

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Inductively Computable Hierarchies and Inductive Algorithmic Complexity

Mark Burgin
Mark Burgin University of California

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