Dynamic programming
Problem optimization method that simplifies a complicated problem by decomposing it into simpler subproblems recursively
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Dynamic programming
Problem optimization method that simplifies a complicated problem by decomposing it into simpler subproblems recursively
Dynamic programming (DP) is both a mathematical optimization method and an algorithmic paradigm. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, such as aerospace engineering and economics.
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From Wikipedia
Dynamic programming (DP) is both a mathematical optimization method and an algorithmic paradigm. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, such as aerospace engineering and 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. If sub-problems can be nested recursively inside larger problems, so that dynamic programming methods are applicable, then there is a relation between the value of the larger problem and the values of the sub-problems. In the optimization literature, this relationship is called the Bellman equation.
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