How Does Dynamic Programming (DP) Work?
- Identify Subproblems: Divide the main problem into smaller, independent subproblems.
- Store Solutions: Solve each subproblem and store the solution in a table or array.
- Build Up Solutions: Use the stored solutions to build up the solution to the main problem.
- Avoid Redundancy: By storing solutions, DP ensures that each subproblem is solved only once, reducing computation time.
Dynamic Programming or DP
Dynamic Programming is a method used in mathematics and computer science to solve complex problems by breaking them down into simpler subproblems. By solving each subproblem only once and storing the results, it avoids redundant computations, leading to more efficient solutions for a wide range of problems. This article provides a detailed exploration of dynamic programming concepts, illustrated with examples.
Table of Content
- What is Dynamic Programming ?
- How Does Dynamic Programming Work?
- Examples of Dynamic Programming
- When to Use Dynamic Programming?
- Approaches of Dynamic Programming
- Dynamic Programming Algorithm
- Advantages of Dynamic Programming
- Applications of Dynamic Programming
- Learn Basic of Dynamic Programming
- Advanced Concepts in Dynamic Programming
- Dynamic Programming Problems