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Abstract

Complexity theory is a means of measuring how complicated it is, or how much computer time it will take, to solve a problem. We measure complexity theory in the following way: Suppose that the formulation of an instance of a problem involves n pieces of data. Then how many steps will it take (as a function of n) to solve the problem? Can we obtain an effective bound on that number of steps that is valid for asymptotically large values of n?

Man propounds negotiations, man accepts the compromise. Very rarely will he squarely push the logic of a fact to its ultimate conclusion in unmitigated act.—Rudyard Kipling

No man, for any considerable period, can wear one face to himself, and another to the multitude, without finally getting bewildered as to which may be the true.—Nathaniel Hawthorne

Light; or, failing that, lightning: the world can take its choice.—Thomas Carlyle

Things and men have always a certain sense, a certain side by which they must be got hold of if one wants to obtain a solid grasp and a perfect command.—Joseph Conrad

In what we really understand, we reason but little.—William Hazlitt

It takes a long time to understand nothing.—Edward Dahlberg

All men naturally desire knowledge.—Aristotle

In all questions of logical analysis, our chief debt is to Frege.—Bertrand Russell and Alfred North Whitehead

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© 2002 Springer Science+Business Media New York

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Krantz, S.G. (2002). Complexity Theory. In: Handbook of Logic and Proof Techniques for Computer Science. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0115-1_12

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  • DOI: https://doi.org/10.1007/978-1-4612-0115-1_12

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-6619-8

  • Online ISBN: 978-1-4612-0115-1

  • eBook Packages: Springer Book Archive

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