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  2. Maze generation algorithm - Wikipedia

    en.wikipedia.org/wiki/Maze_generation_algorithm

    Animation of generator using depth-first search A different animation of a generator using depth-first search. This algorithm, also known as the "recursive backtracker" algorithm, is a randomized version of the depth-first search algorithm.

  3. Sudoku solving algorithms - Wikipedia

    en.wikipedia.org/wiki/Sudoku_solving_algorithms

    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.

  4. Backtracking - Wikipedia

    en.wikipedia.org/wiki/Backtracking

    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.

  5. Backjumping - Wikipedia

    en.wikipedia.org/wiki/Backjumping

    In constraint programming and SAT solving, backjumping (also known as non-chronological backtracking [1] or intelligent backtracking [2]) is an enhancement for backtracking algorithms which reduces the search space.

  6. DPLL algorithm - Wikipedia

    en.wikipedia.org/wiki/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 conjunctive normal form, i.e. for solving the CNF-SAT problem.

  7. Backtracking line search - Wikipedia

    en.wikipedia.org/wiki/Backtracking_line_search

    In (unconstrained) mathematical optimization, a backtracking line search is a line search method to determine the amount to move along a given search direction.Its use requires that the objective function is differentiable and that its gradient is known.

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