by Johan Håstad
Number of pages: 130
The main idea of the course has been to give the broad picture of modern complexity theory. To define the basic complexity classes, give some examples of each complexity class and to prove the most standard relations. The set of notes does not contain the amount of detail wanted from a text book. I have taken the liberty of skipping many boring details and tried to emphasize the ideas involved in the proofs. Probably in many places more details would be helpful and I would he grateful for hints on where this is the case. Most of the notes are at a fairly introductory level but some of the section contain more advanced material. This is in particular true for the section on pseudorandom number generators and the proof that IP = PSPACE. Anyone getting stuck in these parts of the notes should not be disappointed.
Home page url
Download or read it online for free here:
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 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 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.
by Leslie Lamport - Addison-Wesley Professional
This book shows how to write unambiguous specifications of complex computer systems. It provides a complete reference manual for the TLA+, the language developed by the author for writing simple and elegant specifications of algorithms and protocols.