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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From the reviews:
"The book is comprehensive and up-to-date. ... The definitions are illustrated by good examples, the proofs are complete and proceed at a convenient pace, the connections and the implications of the results are spelled out clearly, the exercises are relevant. The book is recommended to specialists as a work of reference, as well as to beginners who want a solid introduction to the theory of parametrized computational problems." (Marius Zimand, Zentralblatt MATH, Vol. 1143, 2008)
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.
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