9. Dynamic Programming II
Learning Objectives
By the end of this chapter, you will be able to:
- Describe how problems can be solved in polynomial versus non-deterministic polynomial time and the effect this has on our ability to develop efficient algorithms
- Implement solutions for both the 0-1 and unbounded variants of the knapsack problem
- Apply the concept of state space reduction to dynamic programming problems
- Determine every shortest path in a weighted graph using approaches that have been optimized by the dynamic programming paradigm
In this chapter, we will build upon our understanding of the dynamic programming approach and examine how it can be used to optimize the problems we discussed in the previous chapter.
Introduction ...
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