What is the difference between memoization and dynamic programming? I think dynamic programming is a subset of memoization. Is it right?
What is the difference between memoization and dynamic programming? I think dynamic programming is
Share
Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
Relevant article on Programming.Guide: Dynamic programming vs memoization vs tabulation
Memoization is a term describing an optimization technique where you cache previously computed results, and return the cached result when the same computation is needed again.
Dynamic programming is a technique for solving problems of recursive nature, iteratively and is applicable when the computations of the subproblems overlap.
Dynamic programming is typically implemented using tabulation, but can also be implemented using memoization. So as you can see, neither one is a “subset” of the other.
A reasonable follow-up question is: What is the difference between tabulation (the typical dynamic programming technique) and memoization?
When you solve a dynamic programming problem using tabulation you solve the problem “bottom up“, i.e., by solving all related sub-problems first, typically by filling up an n-dimensional table. Based on the results in the table, the solution to the “top” / original problem is then computed.
If you use memoization to solve the problem you do it by maintaining a map of already solved sub problems. You do it “top down” in the sense that you solve the “top” problem first (which typically recurses down to solve the sub-problems).
A good slide from
here(link is now dead, slide is still good though):Additional resources: