Picture 1 of 1

Stock photo

Computability and Complexity Theory (Texts in Computer Science) - Picture 1 of 1

Graduate Texts in Computer Science: Computability and Complexity Theory by Steven Homer and Alan L. Selman (2001, Hardcover)

baystatebooks (32409)

99% positive feedback

Price:

US $11.21

(inclusive of GST)

ApproximatelyS$ 14.43

+ $22.96 shipping

Estimated delivery Tue, 1 Jul - Thu, 10 Jul

Returns:

30 days return. Buyer pays for return shipping. If you use an eBay shipping label, it will be deducted from your refund amount.

Condition:

Good

About this product

Product Identifiers

PublisherSpringer

ISBN-100387950559

ISBN-139780387950556

eBay Product ID (ePID)1855890

Product Key Features

Number of PagesXiii, 194 Pages

LanguageEnglish

Publication NameComputability and Complexity Theory

SubjectMachine Theory, Computer Science, Logic

Publication Year2001

TypeTextbook

AuthorSteven Homer, Alan L. Selman

Subject AreaMathematics, Computers

SeriesGraduate Texts in Computer Science

FormatHardcover

Dimensions

Item Weight22.6 Oz

Item Length9.3 in

Item Width7 in

Additional Product Features

Intended AudienceCollege Audience

LCCN00-053829

Reviews"The difference between this new introductory graduate textbook in theoretical computer science and other texts is that the authors have chosen to concentrate on computability theory and computational complexity theory. They motivate this focus by pointing out that most students have been introduced to the theory of automata and formal languages as undergraduates. The topics are treated in depth and in full formal detail. Explicit homework assignments are tightly integrated into the exposition of the material." --Computing Reviews

Dewey Edition21

IllustratedYes

Dewey Decimal004

Table Of Content1. Preliminaries; 2. Introduction to Computability; 3. Undecidability; 4. Introduction to Complexity Theory; 5. Basic Results; 6. Nondeterminism and NP-Completeness; 7. Relative Computability

SynopsisThe theory of computing provides computer science with concepts, models, and formalisms for reasoning about the resources needed to carry out computations, and the efficiency of the computations. It provides tools to measure the difficulty of combinatorial problems both absolutely, and in comparison with other problems. This book contains material that should be core knowledge in the theory of computation for all graduate students in computer science. This comprehensive introduction begins with classical computability theory and develops complexity theory on top of that., Intended for use in an introductory graduate course in theoretical computer science, this text contains material that should be core knowledge in the theory of computation for all graduates in computer science. It is self-contained and is best suited for a one semester course. The text starts with classical computability theory which forms the basis for complexity theory. This has the pedagogical advantage that students learn a qualitative subject before advancing to a quantitative one. Since this is a graduate course, students should have some knowledge of such topics as automata theory, formal languages, computability theory or complexity theory.

LC Classification NumberQA76.H6236 2001