| 书目名称 | Computability and Complexity Theory | | 编辑 | Steven Homer,Alan L. Selman | | 视频video | | | 丛书名称 | Texts in Computer Science | | 图书封面 |  | | 描述 | The theory of computing provides computer science with concepts, models, and formalisms for reasoning about both the resources needed to carry out computa tions and the efficiency of the computations that use these resources. lt provides tools to measure the difficulty of combinatorial problems both absolutely and in comparison with other problems. Courses in this subject help students gain an alytic skills and enable them to recognize the limits of computation. For these reasons, a course in the theory of computing is usually required in the graduate computer science curriculum. The barder question to address is which topics such a course should cover. We believe that students should learn the fundamental models of computation, the limitations of computation, and the distinctions between feasible and intractable. In particular, the phenomena ofNP-completeness and NP-hardness have pervaded much of science and transformed computer science. One option is to survey a large nurober of theoretical subjects, typically focusing on automata and formal languages. However, these subjects are less important to theoretical computer sci ence, and to computer science as a whole, now than in t | | 出版日期 | Textbook 20011st edition | | 关键词 | Automat; automata; automata theory; complexity; complexity theory; computability theory; computer; computer | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-3544-4 | | isbn_ebook | 978-1-4757-3544-4Series ISSN 1868-0941 Series E-ISSN 1868-095X | | issn_series | 1868-0941 | | copyright | Springer Science+Business Media New York 2001 |
The information of publication is updating
|
|
发表于 2025-3-21 16:43:01
