Explain dynamic programming to a biology majorwhat it is, how it works, and why it is valuable.
Answers
Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineeringto economics. In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively. Likewise, in computer science, if a problem can be solved optimally by breaking it into sub-problems and then recursively finding the optimal solutions to the sub-problems, then it is said to have optimal substructure.
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Answer:
Dynamic programming is usually, but not always, used to solve optimization problems, similar to greedy algorithms. Unlike greedy algorithms, which require a greedy choice property to be valid, dynamic programming works on a range of problems in which locally optimal choices do not produce globally optimal results.