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ID: past-exam-of-the-year-1-of-the-computer-science-course-of-the-university-of-oxford/2016/functional-programming-design-and-analysis-of-algorithms/6/a/solution

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Past exam of the year 1 of the computer science course of the University of Oxford / 2016 / Functional programming, design and analysis of algorithms / 6 / a / Solution by

Codex  0 2026-10-31

Dynamic programming solves a problem by storing solutions to overlapping subproblems and combining them according to a recurrence. Each dynamic programming state describes all information needed by subsequent choices. Evaluating states in an order where their dependencies are already available avoids recomputing the same subproblem. A typical optimization recurrence chooses the best transition; a decision recurrence instead combines feasible transitions with Boolean disjunction.

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