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Backtracking is a class of algorithms for finding solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons a candidate ("backtracks") as soon as it determines that the candidate cannot possibly be completed to a valid solution.
It is particularly useful for efficiently implementing backtracking algorithms, such as Knuth's Algorithm X for the exact cover problem. [1] Algorithm X is a recursive , nondeterministic , depth-first , backtracking algorithm that finds all solutions to the exact cover problem.
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 look-ahead are to choose a variable to evaluate next and to choose the order of values to assign to it.
Some hobbyists have developed computer programs that will solve Sudoku puzzles using a backtracking algorithm, which is a type of brute force search. [3] Backtracking is a depth-first search (in contrast to a breadth-first search), because it will completely explore one branch to a possible solution before moving to another branch.
The most used techniques are variants of backtracking, constraint propagation, and local search. These techniques are also often combined, as in the VLNS method, and current research involves other technologies such as linear programming. [14] Backtracking is a recursive algorithm. It maintains a partial assignment of the variables.
Constraint satisfaction toolkits are software libraries for imperative programming languages that are used to encode and solve a constraint satisfaction problem. Cassowary constraint solver, an open source project for constraint satisfaction (accessible from C, Java, Python and other languages). Comet, a commercial programming language and toolkit
The DPLL algorithm enhances over the backtracking algorithm by the eager use of the following rules at each step: Unit propagation If a clause is a unit clause , i.e. it contains only a single unassigned literal, this clause can only be satisfied by assigning the necessary value to make this literal true.
Constraint programming (CP) [1] is a paradigm for solving combinatorial problems that draws on a wide range of techniques from artificial intelligence, computer science, and operations research. In constraint programming, users declaratively state the constraints on the feasible solutions for a