Abstract Algorithms 3—Dynamic Programming


After reading this chapter, you should understand:

  • Dynamic Programming—principles and applications
  • Dynamic Programming—its power and limitations
  • The Principle of Optimality
  • Dynamic Programming and Greedy Strategies—Where to use what
  • Memoization
  • Significance of Optimal Substructure and Overlapping Sub-Problems
  • Shortest Path Algorithms—General Cases Dijkstra’s Algorithm, Bellman-Ford Algorithm, Floyd-Warshall Algorithm
  • Maximum Flow Problems: Ford-Fulkerson Method

A computer is essentially a trained squirrel: acting on reflex, thoughtlessly running back and forth and storing away nuts until some other stimulus makes it do somthing else.

—Ted Nelson

Nature laughs at the difficulties of ...

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