Constraint Satisfaction Problems over Numeric Domains∗ Manuel Bodirsky1 and Marcello Mamino2 1 Institut für Algebra, TU Dresden, Dresden, Germany
[email protected] 2 Institut für Algebra, TU Dresden, Dresden, Germany
[email protected] Abstract We present a survey of complexity results for constraint satisfaction problems (CSPs) over the integers, the rationals, the reals, and the complex numbers. Examples of such problems are feasibility of linear programs, integer linear programming, the max-atoms problem, Hilbert’s tenth problem, and many more. Our particular focus is to identify those CSPs that can be solved in polynomial time, and to distinguish them from CSPs that are NP-hard. A very helpful tool for obtaining complexity classifications in this context is the concept of a polymorphism from universal algebra. 1998 ACM Subject Classification F.2.2 Nonnumerical Algorithms and Problems Keywords and phrases Constraint satisfaction problems, Numerical domains Digital Object Identifier 10.4230/DFU.Vol7.15301.79 1 Introduction Many computational problems from many different research areas in theoretical computer science can be formulated as Constraint Satisfaction Problems (CSPs) where the variables might take values from an infinite domain. There is a considerable literature about the computational complexity of particular infinite domain CSPs, but there are only few system- atic complexity results. Most of these results belong to two research directions. One is the development of the universal-algebraic approach, which has been so successful for studying the complexity of finite-domain constraint satisfaction problems. The other direction is to study constraint satisfaction problems over some of the most basic and well-known infinite domains, such as the numeric domains Z (the integers), Q (the rational numbers), R (the reals), or C (the complex numbers), and to focus on constraint relations that are first-order definable from usual addition and multiplication on those domains.