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Updated on 20th June, 2024 , 3 min read
Backtracking algorithms are like problem-solving strategies which help in exploring different options to find the best solution possible. They work by trying out different paths and if one doesn’t work, it backtracks together with tries another until they find the right one. It is to solve a puzzle by testing various pieces until they fit in together perfectly.
Backtracking is a problem-solving algorithmic technique which involves finding a solution incrementally by trying different options and also undoing them if they lead to a dead end.
It is very common to use in this situation where one needs to explore quite a few possibilities to solve problems, like searching for paths in a maze or solving puzzles like Sudoku. When a dead end is about to be reached, the algorithm backtracks to the previous decision point and tours a different path until a solution is found and all possibilities have been exhausted.
A backtracking algorithm works by recursively exploring all possible solutions to the problem. It starts by choosing an early solution, and then it finds all possible extensions of the solution. If an extension drives to a solution, the algorithm gets back that solution. If an extension does not lead the way to a solution, the algorithm backtracks to the forgoing solution and tries a different extension.
Backtracking algorithms are one of the best used to solve problems that have the following characteristics:
When one has multiple choices, then one can make the decisions from the available choices. In the backing cases, one needs to use the backtracking algorithm: A piece of enough information is not available to make the best choice, so one uses the backtracking strategy to try out all the possible solutions available.
Each decision guides a new set of choices. Then again, one backtracks to make a new decision. In these cases, one needs to use the backtracking strategy.
These terms are related to the backtracking are:
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