Książka Parameterized Complexity Theory J. Flum

Parameterized Complexity Theory

Autor: J. Flum, M. Grohe
Język: Angielski
Oprawa: Miękka
Wydawca: Springer, Berlin
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
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This book is a state-of-the-art introduction into both algorithmic techniques for fixed-parameter tr...

Informacje o książce

Autor
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2010
strony
495
EAN
9783642067570
ISBN
3642067573
Enbook ID
01651970
Waga
761
Wymiary
155 x 235 x 26

Pełny opis

This book is a state-of-the-art introduction into both algorithmic techniques for fixed-parameter tractability and the structural theory of parameterized complexity classes. It presents detailed proofs of recent advanced results that have not appeared in book form before and replaces the earlier publication "Parameterized Complexity" by Downey and Fellows as the definitive book on this subject. The book will interest computer scientists, mathematicians and graduate students engaged with algorithms and problem complexity.Parameterized complexity theory is a recent branch of computational complexity theory that provides a framework for a refined analysis of hard algorithmic problems. The central notion of the theory, fixed-parameter tractability, has led to the development of various new algorithmic techniques and a whole new theory of intractability.§This book is a state-of-the-art introduction to both algorithmic techniques for fixed-parameter tractability and the structural theory of parameterized complexity classes, and it presents detailed proofs of recent advanced results that have not appeared in book form before. Several chapters are each devoted to intractability, algorithmic techniques for designing fixed-parameter tractable algorithms, and bounded fixed-parameter tractability and subexponential time complexity. The treatment is comprehensive, and the reader is supported with exercises, notes, a detailed index, and some background on complexity theory and logic.§The book will be of interest to computer scientists, mathematicians and graduate students engaged with algorithms and problem complexity.

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