Backtracking is a powerful problem-solving technique in computer science and mathematics. Imagine you're solving a maze on paper. You start drawing a path but soon realize you've hit a dead end. What do you do? You backtrack to the last intersection and try a different path. This is essentially what backtracking algorithms do in computing.
Backtracking is particularly useful for problems where we need to find all possible solutions or an optimal solution among many possibilities. It's commonly applied to puzzles like Sudoku, problems like "N-Queens," or to generating all possible permutations or combinations of a set.
Generally, these algorithms have poor efficiency, often with exponential or even factorial time complexity. Calculating these complexities can be very challenging, so we won't focus on detailed complexity analysis in this lesson. Instead, we'll concentrate on understanding the concept and implementation of backtracking. Being able to approach and solve these problems is already a significant achievement.
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