Techniques to solve Dynamic Programming Problems
Break down the given problem in order to begin solving it. If you see that the problem has already been solved, return the saved answer. If it hasn’t been solved, solve it and save it. This is usually easy to think of and very intuitive, This is referred to as Memoization.
Analyze the problem and see in what order the subproblems are solved, and work your way up from the trivial subproblem to the given problem. This process ensures that the subproblems are solved before the main problem. This is referred to as Bottom-up Dynamic Programming.
Types of the approach of dynamic programming algorithm
How Does Dynamic Programming Work?
Dynamic programming, popularly known as DP, is a method of solving problems by breaking them down into simple, overlapping subproblems and then solving each of the subproblems only once, storing the solutions to the subproblems that are solved to avoid redundant computations. This technique is useful for optimization-based problems, where the goal is to find the most optimal solution among all possible set of solutions.
Table of Content
- What is Dynamic Programming?
- Dynamic Programming Characteristics
- Techniques to solve Dynamic Programming Problems
- Understanding Dynamic Programming With Examples
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