This textbook is uniquely written with dual purpose. It covers core material in the foundations of computing for graduate students in computer science and also provides an introduction to some more advanced topics for those intending further study in the area. The book contains an invaluable collection of lectures for first-year graduates on the theory of computation, focusing primarily on computational complexity theory. It also deals with the classification of computational problems in terms of their inherent complexity.
It incorporates rigorous treatment of computational models, such as deterministic, nondeterministic, and alternating Turing machines; circuits; probabilistic machines; interactive proof systems; automata on infinite objects; and logical formalisms. Features include more than 40 lectures for first year graduate students, and a dozen homework sets and exercises. The book is aimed at advanced undergraduates and first-year graduates in Computer Science or Mathematics.
In these early years of the 21st Century, researchers in the field of computing are delving ever further into the new possibilities of the science and to the primary tools that form its foundations. The theory behind computation has never been more important.
Theory of Computation is a unique textbook that serves the dual purposes of covering core material in the foundations of computing, as well as providing an introduction to some more advanced contemporary topics. This innovative text focuses primarily, although by no means exclusively, on computational complexity theory: the classification of computational problems in terms of their inherent complexity. It incorporates rigorous treatment of computational models, such as deterministic, nondeterministic, and alternating Turing machines; circuits; probabilistic machines; interactive proof systems; automata on infinite objects; and logical formalisms. Although the complexity universe stops at polynomial space in most treatments, this work also examines higher complexity levels all the way up through primitive and partial recursive functions and the arithmetic and analytic hierarchies.
Topics and features:
Provides in-depth coverage of both classical and contemporary approaches in one useful, concise volume
Organized into readily applicable, self-contained primary and secondary lectures
Contains more than 180 homework exercises of varying difficulty levels, many with hints and solutions
Includes approximation and inapproximation results, and some lower bounds
Treats complexity theory and classical recursion theory in a unified framework
Advanced undergraduates and first-year graduates in Computer Science or Mathematics will receive a thorough grounding in the core theory of computation and computational complexity, as well as an introduction to advanced contemporary topics for further study. Computing professionals and other scientists interested in learning more about these topics will also find this text extremely useful.
Prof. Dexter Kozen teaches at Cornell University, Ithaca, New York, and has comprehensively class-tested this books content. He authored the highly successfulAutomata and Computability, which offers an introduction to the basic theoretical models of computability, andThe Design and Analysis of Algorithms.
