How does backtracking compare to other algorithms?

Can you explain how backtracking works in algorithms?

Backtracking is a problem-solving technique that incrementally builds candidates for solutions and abandons a candidate as soon as it is determined that it cannot lead to a valid solution.

How does backtracking compare to other algorithms like dynamic programming?

Backtracking is often less efficient than dynamic programming because it explores all possible solutions, while dynamic programming optimizes by storing results of subproblems.

Are there specific problems where backtracking is preferred?

Yes, backtracking is particularly useful for constraint satisfaction problems, such as puzzles, combinatorial problems, and games like Sudoku.

What are the limitations of using backtracking?

The main limitations include its potential for high time complexity and inefficiency in large search spaces, as it may explore many unnecessary paths.