Logo

Introduction to Complexity Theory

Introduction to Complexity Theory
by


Number of pages: 375

Description:
Complexity Theory is a central field of Theoretical Computer Science, with a remarkable list of celebrated achievements as well as a very vibrant present research activity. The field is concerned with the study of the intrinsic complexity of computational tasks, and this study tend to aim at generality: It focuses on natural computational resources, and the effect of limiting those on the class of problems that can be solved. These lecture notes were taken by students attending my year-long introductory course on Complexity Theory, given in 1998-99 at the Weizmann Institute of Science. The course was aimed at exposing the students to the basic results and research directions in the field. The focus was on concepts and ideas, and complex technical proofs were avoided. It was assumed that students have taken a course in computability, and hence are familiar with Turing Machines.

Home page url

Download or read it online for free here:
Download link
(2.3MB, PDF)

Similar books

Book cover: Think Complexity: Complexity Science and Computational ModelingThink Complexity: Complexity Science and Computational Modeling
by - 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.
(7917 views)
Book cover: Lecture Notes on Computational ComplexityLecture Notes on Computational Complexity
by
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.
(13742 views)
Book cover: Communication Complexity (for Algorithm Designers)Communication Complexity (for Algorithm Designers)
by - Stanford University
The two biggest goals of the course are: 1. Learn several canonical problems that have proved the most useful for proving lower bounds; 2. Learn how to reduce lower bounds for fundamental algorithmic problems to communication complexity lower bounds.
(4700 views)
Book cover: Algorithmic Randomness and ComplexityAlgorithmic Randomness and Complexity
by - 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.
(8708 views)