Abstract
Computational Complexity measures the amount of computational resources, such as time and space, that are needed, as a function of the size of the input, to compute a query. This chapter introduces the reader to complexity theory. We define the complexity measures and complexity classes that we study in the rest of the book. We also explain some of their basic properties, complete problems, and interrelationships.
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Notes
The usual definition in complexity theory writes t(n) as the function t′(n), a polynomially-related function of the length of the encoding of the input. We use n to be the size of the universe of the input structure and measure all sizes in this uniform way.
Those readers who believe that the class BPP properly contains P should change this sentence to, “⋯a proper subset of BPP.”
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© 1999 Springer Science+Business Media New York
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Immerman, N. (1999). Background in Complexity. In: Descriptive Complexity. Graduate Texts in Computer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0539-5_3
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DOI: https://doi.org/10.1007/978-1-4612-0539-5_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-6809-3
Online ISBN: 978-1-4612-0539-5
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