Probability and Algorithms

Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the worst-case or average-case analyses.This book surveys both of these emerging areas on the interface of the mathematical sciences and computer science. It is designed to attract new researchers to this area and provide them with enough background to begin explorations of their own.Table of ContentsFront Matter1 Introduction2 Simulated Annealing3 Approximate Counting Via Markov Chains4 Probabilistic Algorithms for Speedup5 Probabilistic Algorithms for Defeating Adversaries6 Pseudorandom Numbers7 Probabilistic Analysis of Packing and Related Partitioning Problems8 Probability and Problems in Euclidean Combinatorial Optimization9 Probabilistic Analysis in Linear Programming10 Randomization in Parallel Algorithms11 Randomly Wired Multistage Networks12 Missing Pieces, Derandomization, and Concluding Remarks