Applying Memoization to Dynamic Programming
Explore how memoization enhances dynamic programming performance by caching results and reducing redundant recursive calls. Understand the rod-cutting problem and apply Kotlin code to find maximum revenue through efficient recursion and memoization.
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Dynamic programming
Dynamic programming is an algorithmic technique that uses memoization to make the execution of recursive calls highly efficient. By caching and reusing the results of a function call, dynamic programming eliminates repetitive recursive calls to functions. So computations that may have exponential time complexity may execute with linear time complexity, thanks to memoization.
In the previous section, we used memoization to compute the Fibonacci number and saw how the technique greatly reduced the ...