Tractability

An overview of the techniques developed to circumvent computational intractability, a key challenge in many areas of computer science.

Many computational problems cannot be solved efficiently according to classical computer science textbooks. Tractability gives a cross-disciplinary overview of the advanced techniques that have been developed in order to solve these 'hard' computational problems, and a unified presentation of the properties that can be exploited to make them tractable.Classical computer science textbooks tell us that some problems are 'hard'. Yet many areas, from machine learning and computer vision to theorem proving and software verification, have defined their own set of tools for effectively solving complex problems. Tractability provides an overview of these different techniques, and of the fundamental concepts and properties used to tame intractability. This book will help you understand what to do when facing a hard computational problem. Can the problem be modelled by convex, or submodular functions? Will the instances arising in practice be of low treewidth, or exhibit another specific graph structure that makes them easy? Is it acceptable to use scalable, but approximate algorithms? A wide range of approaches is presented through self-contained chapters written by authoritative researchers on each topic. As a reference on a core problem in computer science, this book will appeal to theoreticians and practitioners alike.