"High-Concentration Chemical Computing Techniques for Solving Hard-To-S" by Vladik Kreinovich and Olac Fuentes

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Departmental Technical Reports (CS)

Title

High-Concentration Chemical Computing Techniques for Solving Hard-To-Solve Problems, and Their Relation to Numerical Optimization, Neural Computing, Reasoning Under Uncertainty, and Freedom Of Choice

Authors

Vladik Kreinovich, University of Texas at El PasoFollow
Olac Fuentes, University of Texas at El PasoFollow

Publication Date

8-2011

Comments

Technical Report: UTEP-CS-11-44

To appear in: Evgeny Katz (ed.), Molecular and Biomolecular Information Processing, Wiley-VCH.

Abstract

Chemical computing -- using chemical reactions to perform computations -- is a promising way to solve computationally intensive problems. Chemical computing is promising because it has the potential of using up to 10^{23} molecules as processors working in parallel -- and thus, has a potential of an enormous speedup. Unfortunately, for hard-to-solve (NP-complete) problems a natural chemical computing approach for solving them is exponentially slow. In this chapter, we show that the corresponding computations can become significantly faster if we use very-high-concentration chemical reactions, concentrations at which the usual equations of chemical kinetics no longer apply. We also show that the resulting method is related to numerical optimization, neural computing, reasoning under uncertainty, and freedom of choice.

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