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International Computing and Combinatorics Conference

COCOON 2002: Computing and Combinatorics pp 171–180Cite as

Solving Constraint Satisfaction Problems with DNA Computing

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2387))

Abstract

We demonstrate how to solve constraint satisfaction problems (CSPs) with DNA computing. Assuming that DNA operations can be faulty, we estimate error probability of our algorithm. We show that for any k-CSP, there is a polynomial-time DNA algorithm with bounded probability of error. Thus, k-CSPs belong to a DNA analogue of BPP.

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Author information

Authors and Affiliations

  1. School of Computer Science, Roosevelt University, 430 South Michigan Ave., Chicago, IL, 60605, USA

    Evgeny Dantsin & Alexander Wolpert

Authors
  1. Evgeny Dantsin
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  2. Alexander Wolpert
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of California, Santa Barbara, California, 93106, USA

    Oscar H. Ibarra

  2. Department of Mathematics, National University of Singapore, Singapore, Singapore, 117543

    Louxin Zhang

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© 2002 Springer-Verlag Berlin Heidelberg

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Dantsin, E., Wolpert, A. (2002). Solving Constraint Satisfaction Problems with DNA Computing. In: Ibarra, O.H., Zhang, L. (eds) Computing and Combinatorics. COCOON 2002. Lecture Notes in Computer Science, vol 2387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45655-4_20

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  • DOI: https://doi.org/10.1007/3-540-45655-4_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43996-7

  • Online ISBN: 978-3-540-45655-1

  • eBook Packages: Springer Book Archive

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