Chapter 2 - CSP solving — An overview

Abstract

This chapter provides an overview of constraint satisfaction problem (CSP) solving techniques, which can roughly be classified into three categories: problem reduction, search, and solution synthesis. It discusses the general characteristics of CSPs and explains how these characteristics could be exploited in solving CSPs. The chapter discusses the features of CSPs, as some of them could be exploited to develop specialized techniques for solving CSPs efficiently. An algorithm is sound if every result that is returned by it is indeed a solution; in CSPs, it means any compound label that is returned by it contains labels for every variable, and this compound label satisfies all the constraints in the problem. Problem reduction is a class of techniques for transforming a CSP into problems that are hopefully easier to solve or recognizable as insoluble. Problem reduction alone does not normally produce solutions; however, it can be extremely useful when used together with search or problem synthesis methods.