Question 1
Why did Richard Bellman choose the term 'Dynamic Programming'?
Question 2
What general scenario is dynamic programming most effectively applied to?
Question 3
How does memoization improve the efficiency of solving subproblems?
Question 4
What is the main advantage of using dynamic programming in algorithm design?
Question 5
Why is the naive recursive approach to computing Fibonacci numbers inefficient?
Question 6
What is the purpose of the layered graph approach in dynamic programming?
Question 7
How does the concept of 'guessing' help in solving subproblems in dynamic programming?
Question 8
For the single source shortest paths problem, what specific graph type is recursion with memoization efficient for?
Question 9
Why are memoization and recursion considered a potent combination in dynamic programming?
Question 10
What role does recursion play in dynamic programming?
Question 11
Which key idea summarizes the strategy of dynamic programming?
Question 12
What does the formulation of 'Delta Definition' in shortest path problems aim to solve?
Question 13
In the context of graph problems, what challenges does dynamic programming face with cycles?
Question 14
What is a critical step when applying dynamic programming principles to solve complex problems?
Question 15
What does the bottom-up approach to solving Fibonacci numbers optimize?