Lectures: MWF 1:00-1:50 in Tech M177
Description:
This course will give an overview of computational complexity including Turing machines, relationships between time and memory, determinism and nondeterminism, reductions and the "P versus NP" problem. We will explore more recent results on randomness including pseudorandom generators and the power of probabilistic proofs.
This course is designed for graduate students or advanced undergraduates. We will assume familiarity with mathematical proofs but no previous knowledge of Turing machines or computational complexity.
Textbook Recommendation: Computers and Intractability: A Guide to the Theory of NP-Completeness by Michael Garey and David Johnson.
On-Line Resources
Complexity Zoo, list and
defintions of hundreds of complexity classes.
Lectures in
Computational Complexity, textbook draft by Jin-Yi Cai
Complexity
Theory: A Modern Approach textbook draft by Sanjeev Arora and Boaz
Barak
Foundations
of Complexity, a series of weblog posts I wrote. Also see this
post on the time and space hierarchies.
Assignments
Lectures:
Each lecture will be scribed by a student in the class.