Learn how to apply dynamic programming to recursive algorithms, such as identifying subproblems, memoizing results, optimizing space, analyzing complexity, and testing and debugging.

One of the trickiest concepts in programming to get your mind around is recursion. In computer science, recursion simply refers to the act of calling a function within itself. More generally, we say ...

Welcome to the Advanced Recursion and Dynamic Programming Practice repository! This project is tailored for individuals with a foundational understanding of recursion and dynamic programming, looking ...

Learn what optimal substructure is, how to identify and use it, and how to deal with its challenges. Optimal substructure is essential for dynamic programming and problem-solving.

Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...

A method for identifying the structure of nonlinear polynomial dynamic models is presented. This approach uses an evolutionary algorithm, genetic programming, in a multiobjective fashion to generate ...