This is a book about computation, something which is ubiquitous in the modern world. More precisely, it examines computability theory and computational complexity theory. Computability theory is the part of mathematics and computer science which seeks to clarify what we mean by computation or algorithm. When is there a computational solution possible to some question? How can we show that none is possible? How computationally hard is the question we are concerned with? Arguably, this area lead to the development of digital computers. (Computational) complexity theory is an intellectual heir of computability theory. Complexity theory is concerned with understanding what resources are needed for computation, where typically we would measure the resources in terms of time and space. Can we perform some task in a feasible number of steps? Can we perform some algorithm with only a limited memory? Does randomness help? Are there standard approaches to overcoming computational difficulty?

Provides a uniquely concise introduction to these subjects Includes numerous examples and exercises Progresses from general to deeper models of computability

Autorentext

Rodney Downey is an Emeritus Professor at Victoria University of Wellington, NZ. He is the co-author of the Springer books, Fundamentals of Parameterized Complexity , and Algorithmic Randomness and Complexity . He has won many prizes for his work, including (twice) the Shoenfield Prize for writing, as well as the Rutherford Medal, New Zealand's premier science award.

Klappentext
The ideas and techniques comprised in the mathematical framework for understanding computation should form part of the standard background of a graduate in mathematics or computer science, as the issues of computability and complexity permeate modern science. This textbook/reference offers a straightforward and thorough grounding in the theory of computability and computational complexity. Among topics covered are basic naive set theory, regular languages and automata, models of computation, partial recursive functions, undecidability proofs, classical computability theory including the arithmetical hierarchy and the priority method, the basics of computational complexity and hierarchy theorems.

Topics and features:

· Explores Conway's undecidability proof of the ``3x+1'' problem using reductions from Register Machines and Fractran

· Offers an accessible account of the undecidability of the exponential version of Hilbert's 10 th problem due to Jones and Matijacevi

· Provides basic material on computable structure, such as computable linear orderings

· Addresses parameterized complexity theory, including applications to algorithmic lower bounds and kernelization lower bounds

· Delivers a short account of generic-case complexity and of smoothed analysis

· Includes bonus material on structural complexity theory and priority arguments in computability theory

This comprehensive textbook will be ideal for advanced undergraduates or beginning graduates, preparing them well for more advanced studies or applications in science. Additionally, it could serve such needs for mathematicians or for scientists working in computational areas, such as biology.

Rodney Downey is an Emeritus Professor at Victoria University of Wellington, NZ. He is the co-author of the Springer books, Fundamentals of Parameterized Complexity , and Algorithmic Randomness and Complexity . He has won many prizes for his work, including (twice) the Shoenfield Prize for writing, as well as the Rutherford Medal, New Zealand's premier science award.

Inhalt

Introduction.- Some Naive Set Theory.- Regular Languages and Finite Automata.- General Models of Computation.- Deeper Computability.- Computational Complexity.- NP- and PSPACE-Completeness.- Some Structural Complexity.- Parameterized Complexity.- Average Case, Smoothed Analysis, and Generic Case.- Complexity.- References. <p