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 Allen B. Downey - Green Tea Press
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.
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.
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 Herbert S. Wilf - AK Peters, Ltd.
An introductory textbook on the design and analysis of algorithms. Recursive algorithms are illustrated by Quicksort, FFT, and fast matrix multiplications. Algorithms in number theory are discussed with some applications to public key encryption.