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M17, Dynamic Programming, Coping with the Limitations of Algorithm Power -…
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Dynamic Programming
Three Basic Examples:
Fibonacci Numbers: Uses a bottom-up approach to store the results of subproblems to avoid redundant calculations.
Shortest Paths in Graphs: Utilizes the Bellman-Ford algorithm to find shortest paths in a weighted graph, handling negative weights.
Matrix Chain Multiplication: Determines the most efficient way to multiply a chain of matrices by finding the order of multiplications that minimizes the number of scalar multiplications.
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Dynamic Programming (DP) is a method for solving complex problems by breaking them down into simpler subproblems and solving each subproblem just once, storing its solution.
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