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Consensus dynamics

Consensus dynamics or agreement dynamics is an area of research lying at the intersection of systems theory and graph theory. A major topic of investigation is the agreement or consensus problem in mu

Cassowary (software)

Cassowary is an incremental constraint solving toolkit that efficiently solves systems of linear equalities and inequalities. Constraints may be either requirements or preferences. Client code specifi

Constraint satisfaction

In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. A

Test functions for optimization

In applied mathematics, test functions, known as artificial landscapes, are useful to evaluate characteristics of optimization algorithms, such as:
* Convergence rate.
* Precision.
* Robustness.
*

Difference-map algorithm

The difference-map algorithm is a search algorithm for general constraint satisfaction problems. It is a meta-algorithm in the sense that it is built from more basic algorithms that perform projection

Narrowing of algebraic value sets

Like logic programming, narrowing of algebraic value sets gives a method of reasoning about the values in unsolved or partially solved equations. Where logic programming relies on resolution, the alge

Constraint graph

In constraint satisfaction research in artificial intelligence and operations research, constraint graphs and hypergraphs are used to represent relations among constraints in a constraint satisfaction

Satisfiability modulo theories

In computer science and mathematical logic, satisfiability modulo theories (SMT) is the problem of determining whether a mathematical formula is satisfiable. It generalizes the Boolean satisfiability

Local consistency

In constraint satisfaction, local consistency conditions are properties of constraint satisfaction problems related to the consistency of subsets of variables or constraints. They can be used to reduc

Constraint logic programming

Constraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program

Decomposition method (constraint satisfaction)

In constraint satisfaction, a decomposition method translates a constraint satisfaction problem into another constraint satisfaction problem that is binary and acyclic. Decomposition methods work by g

Schaefer's dichotomy theorem

In computational complexity theory, a branch of computer science, Schaefer's dichotomy theorem states necessary and sufficient conditions under which a finite set S of relations over the Boolean domai

SWI-Prolog

SWI-Prolog is a free implementation of the programming language Prolog, commonly used for teaching and semantic web applications. It has a rich set of features, libraries for constraint logic programm

Regular constraint

In artificial intelligence and operations research, a regular constraint is a kind of . It can be used to solve a particular type of puzzle called a nonogram or logigrams.

Minion (solver)

Minion is a solver for constraint satisfaction problems. Unlike constraint programming toolkits, which expect users to write programs in a traditional programming language like C++, Java or Prolog, Mi

AC-3 algorithm

In constraint satisfaction, the AC-3 algorithm (short for Arc Consistency Algorithm #3) is one of a series of algorithms used for the solution of constraint satisfaction problems (or CSP's). It was de

Constraint satisfaction dual problem

The dual problem is a reformulation of a constraint satisfaction problem expressing each constraint of the original problem as a variable. Dual problems only contain binary constraints, and are theref

JaCoP (solver)

JaCoP is a constraint solver for constraint satisfaction problems. It is written in Java and it is provided as a Java library. JaCoP has an interface to the MiniZinc and AMPL modeling languages. Its m

Traveling tournament problem

The traveling tournament problem (TTP) is a mathematical optimization problem. The question involves scheduling a series of teams such that: 1.
* Each team plays every other team twice, once at home

Symmetry-breaking constraints

In the field of mathematics called combinatorial optimization, the method of symmetry-breaking constraints can be used to take advantage of symmetries in many constraint satisfaction and optimization

DPLL(T)

In computer science, DPLL(T) is a framework for determining the satisfiability of SMT problems. The algorithm extends the original SAT-solving DPLL algorithm with the ability to reason about an arbitr

Constraint satisfaction problem

Constraint satisfaction problems (CSPs) are mathematical questions defined as the set of objects whose state must satisfy a number of constraints or/ limitations. CSPs represent a entities in a proble

Barrier function

In constrained optimization, a field of mathematics, a barrier function is a continuous function whose value on a point increases to infinity as the point approaches the boundary of the feasible regio

Min-conflicts algorithm

In computer science, the min-conflicts algorithm is a search algorithm or heuristic method to solve constraint satisfaction problems. Given an initial assignment of values to all the variables of a co

Intertemporal budget constraint

In economics and finance, an intertemporal budget constraint is a constraint faced by a decision maker who is making choices for both the present and the future. The term intertemporal is used to desc

Complexity of constraint satisfaction

The complexity of constraint satisfaction is the application of computational complexity theory on constraint satisfaction. It has mainly been studied for discriminating between tractable and intracta

Backjumping

In backtracking algorithms, backjumping is a technique that reduces search space, therefore increasing efficiency. While backtracking always goes up one level in the search tree when all values for a

Algorithm selection

Algorithm selection (sometimes also called per-instance algorithm selection or offline algorithm selection) is a meta-algorithmic technique to choose an algorithm from a portfolio on an instance-by-in

Region connection calculus

The region connection calculus (RCC) is intended to serve for qualitative spatial representation and reasoning. RCC abstractly describes regions (in Euclidean space, or in a topological space) by thei

Distributed constraint optimization

Distributed constraint optimization (DCOP or DisCOP) is the distributed analogue to constraint optimization. A DCOP is a problem in which a group of agents must distributedly choose values for a set o

Kaleidoscope (programming language)

The Kaleidoscope programming language is a constraint programming language embedding constraints into an imperative object-oriented language. It adds keywords always, once, and assert..during (formerl

WalkSAT

In computer science, GSAT and WalkSAT are local search algorithms to solve Boolean satisfiability problems. Both algorithms work on formulae in Boolean logic that are in, or have been converted into c

Hybrid algorithm (constraint satisfaction)

Within artificial intelligence and operations research for constraint satisfaction a hybrid algorithm solves a constraint satisfaction problem by the combination of two different methods, for example

GNU Prolog

GNU Prolog (also called gprolog) is a compiler developed by Daniel Diaz with an interactive debugging environment for Prolog available for Unix, Windows, Mac OS X and Linux. It also supports some exte

Reasoning system

In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play a

Look-ahead (backtracking)

In backtracking algorithms, look ahead is the generic term for a subprocedure that attempts to foresee the effects of choosing a branching variable to evaluate one of its values. The two main aims of

Allen's interval algebra

For the type of boolean algebra called interval algebra, see Boolean algebra (structure) Allen's interval algebra is a calculus for temporal reasoning that was introduced by James F. Allen in 1983. Th

Constrained optimization

In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function with respect to some variables in the presen

Local search (constraint satisfaction)

In constraint satisfaction, local search is an incomplete method for finding a solution to a problem. It is based on iteratively improving an assignment of the variables until all constraints are sati

Interchangeability algorithm

In computer science, an interchangeability algorithm is a technique used to more efficiently solve constraint satisfaction problems (CSP). A CSP is a mathematical problem in which objects, represented

Constraint programming

Constraint programming (CP) is a paradigm for solving combinatorial problems that draws on a wide range of techniques from artificial intelligence, computer science, and operations research. In constr

Ordered graph

An ordered graph is a graph with a total order over its nodes. In an ordered graph, the parents of a node are the nodes that are adjacent to it and precede it in the ordering. More precisely, is a par

Weighted constraint satisfaction problem

In artificial intelligence and operations research, a Weighted Constraint Satisfaction Problem (WCSP) is a generalization of a constraint satisfaction problem (CSP) where some of the constraints can b

Backmarking

In constraint satisfaction, backmarking is a variant of the backtracking algorithm. Backmarking works like backtracking by iteratively evaluating variables in a given order, for example, . It improves

Geometric constraint solving

Geometric constraint solving is constraint satisfaction in a computational geometry setting, which has primary applications in computer aided design. A problem to be solved consists of a given set of

BNR Prolog

BNR Prolog, also known as CLP(BNR) is a declarative constraint logic programming language based on relational interval arithmetic developed at Bell-Northern Research in the 1980s and 1990s. Embedding

Constraint inference

In constraint satisfaction, constraint inference is a relationship between constraints and their consequences. A set of constraints entails a constraint if every solution to is also a solution to . In

Basis pursuit

Basis pursuit is the mathematical optimization problem of the form where x is a N-dimensional solution vector (signal), y is a M-dimensional vector of observations (measurements), A is a M × N transfo

Constraint learning

In constraint satisfaction backtracking algorithms, constraint learning is a technique for improving efficiency. It works by recording new constraints whenever an inconsistency is found. This new cons

DPLL algorithm

In logic and computer science, the Davis–Putnam–Logemann–Loveland (DPLL) algorithm is a complete, backtracking-based search algorithm for deciding the satisfiability of propositional logic formulae in

Davis–Putnam algorithm

The Davis–Putnam algorithm was developed by Martin Davis and Hilary Putnam for checking the validity of a first-order logic formula using a resolution-based decision procedure for propositional logic.

Hidden transformation

The hidden transformation reformulates a constraint satisfaction problem in such a way all constraints have at most two variables. The new problem is satisfiable if and only if the original problem wa

Nurse scheduling problem

The nurse scheduling problem (NSP), also called the nurse rostering problem (NRP), is the operations research problem of finding an optimal way to assign nurses to shifts, typically with a set of hard

Gecode

Gecode (for Generic Constraint Development Environment) is a software library for solving Constraint satisfaction problems. It is programmed in C++ and distributed as free software under the permissiv

CLP(R)

CLP(R) is a declarative programming language. It stands for constraint logic programming (Real) where real refers to the real numbers. It can be considered and is generally implemented as a superset o

ILOG

ILOG S.A. was an international software company purchased and incorporated into IBM announced in January, 2009. It created enterprise software products for supply chain, business rule management, visu

Binary constraint

A binary constraint, in mathematical optimization, is a constraint that involves exactly two variables. For example, consider the n-queens problem, where the goal is to place n chess queens on an n-by

Constraint composite graph

The constraint composite graph is a node-weighted undirected graph associated with a given combinatorial optimization problem posed as a weighted constraint satisfaction problem. Developed and introdu

Hierarchical constraint satisfaction

In artificial intelligence and operations research, hierarchical constraint satisfaction (HCS) is a method of handling constraint satisfaction problems where the variables have large domains by exploi

Constraint (mathematics)

In mathematics, a constraint is a condition of an optimization problem that the solution must satisfy. There are several types of constraints—primarily equality constraints, inequality constraints, an

Max/min CSP/Ones classification theorems

In computational complexity theory, a branch of computer science, the Max/min CSP/Ones classification theorems state necessary and sufficient conditions that determine the complexity classes of proble

Chaff algorithm

Chaff is an algorithm for solving instances of the Boolean satisfiability problem in programming. It was designed by researchers at Princeton University, United States. The algorithm is an instance of

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