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Dynamic Programming and Greedy: Knowing Which One Applies

Both techniques replace exponential search with something polynomial, and both fail on problems without the right structure. This path builds the recognition skill rather than a catalogue of recurrences: optimal substructure and where it breaks, choosing a state and deriving the running time from it, the exchange argument and the matroid theorem that says exactly when greedy is guaranteed, and a decision procedure to run on a problem you have never seen before.

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Lessons, in order

  1. 1
    Computer Science
    Optimal Substructure: The Property Both Techniques Need
    Start
  2. 2
    Computer Science
    Designing a Dynamic Program: State, Transition, Order
    Start
  3. 3
    Computer Science
    Greedy: Proving a Local Choice Is Globally Right
    Start
  4. 4
    Computer Science
    Which Technique Applies, and How to Tell
    Start