Computability and Complexity
Publisher: Wikibooks 2010
This book is intended as an introductory textbook in Computability Theory and Complexity Theory, with an emphasis on Formal Languages. Its target audience is Computer Science and Math students with some background in programming, data structures, and discrete math, such as a sophomore in a Computer Science program.
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by Sanjeev Arora, Boaz Barak - Cambridge University Press
The book provides an introduction to basic complexity classes, lower bounds on resources required to solve tasks on concrete models such as decision trees or circuits, derandomization and pseudorandomness, proof complexity, quantum computing, etc.
by Luca Trevisan
Notes from a graduate courses on Computational Complexity. The first 15 lectures cover fundamentals, the remaining is advanced material: Hastad's optimal inapproximability results, lower bounds for parity in bounded depth-circuits, and more.
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 Alexander Shen - arXiv.org
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.