Think Complexity: Complexity Science and Computational Modeling
by Allen B. Downey
Publisher: Green Tea Press 2012
Number of pages: 146
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. The book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations.
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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 Oded Goldreich
Complexity theory is the study of the intrinsic complexity of computational tasks. The book is aimed at exposing the students to the basic results and research directions in the field. The focus was on concepts, complex technical proofs were avoided.
by Johan Håstad
This set of notes gives the broad picture of modern complexity theory, defines the basic complexity classes, gives some examples of each complexity class and proves the most standard relations. The author emphasizes the ideas involved in the proofs.
by Neil D. Jones - The MIT Press
The author builds a bridge between computability and complexity theory and other areas of computer science. Jones uses concepts familiar from programming languages to make computability and complexity more accessible to computer scientists.