Optimal path cost and path in a matrix . Dynamic programming

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Finding optimal path cost and path in a matrix using dynamic programming.

Dynamic programming is a technique to solve problems by breaking them down into smaller subproblems and solving them recursively.
In this case, we can use dynamic programming to find the optimal path cost and path in a matrix.
We can start by defining a 2D array to store the minimum cost of reaching each cell in the matrix.
Then, we can use a recursive function to calculate the minimum cost of reaching the destination cell from each cell in the matrix.
Finally, we can backtrack from the destination cell to the source cell to find the optimal path.
Example: Given a matrix of size m x n, find the minimum cost of reaching the bottom-right cell from the top-left cell.
Example: Given a matrix of size m x n, find the optimal path from the top-left cell to the bottom-right cell with minimum cost.

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