Computational Complexity: A Conceptual Perspective
by Oded Goldreich
Publisher: Cambridge University Press 2008
Number of pages: 632
This book offers a comprehensive perspective to modern topics in complexity theory, which is a central field of the theoretical foundations of computer science. It addresses the looming question of what can be achieved within a limited amount of time with or without other limited natural computational resources. The book can be used as an introduction for advanced undergraduate and graduate students as either a textbook or for self-study, or to experts, since it provides expositions of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness and probabilistic proof systems.
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by R. G. Downey, D. R. Hirschfeldt - Springer
Computability and complexity theory are two central areas of research in theoretical computer science. This book provides a systematic, technical development of algorithmic randomness and complexity for scientists from diverse fields.
by Karl Petersen - University of North Carolina
These notes provide an introduction to the subject of measure-preserving dynamical systems, discussing the dynamical viewpoint; how and from where measure-preserving systems arise; the construction of measures and invariant measures; etc.
by Allen Downey - Green Tea Press
This book is about data structures and algorithms, intermediate programming in Python, complexity science and the philosophy of science. The book covers Graphs, Analysis of algorithms, Scale-free networks, Cellular Automata, Agent-based models, etc.
by Ian Parberry - Prentice Hall
The rapid growth of parallel complexity theory has led to a proliferation of parallel machine models. This book presents a unified theory of parallel computation based on a network model. It is the first such synthesis in book form.