What are backtracking algorithms and how do they work?

What are backtracking algorithms and how do they work?

Backtracking algorithms are a class of algorithms used for solving problems incrementally, by trying partial solutions and then abandoning them if they are not valid. They are often used in constraint satisfaction problems, such as puzzles, games, and combinatorial optimization.

Can you give me an example of a problem that uses backtracking?

Sure! A classic example is the N-Queens problem, where the goal is to place N queens on an N×N chessboard so that no two queens threaten each other. Backtracking helps in exploring possible placements and retracting when a conflict arises.

How does backtracking differ from other algorithms?

Backtracking differs from other algorithms like brute force by not exploring all possible solutions. Instead, it eliminates paths that are not viable, making it more efficient for certain problems.

What are some common applications of backtracking?

Common applications include solving puzzles like Sudoku, generating permutations and combinations, and pathfinding problems in graphs.