Lecture 2b: Solving Search Problems - Parte2

What is the total number of nodes generated in the worst case in an iterative deepening search with b=10 and d=5?

• 100

• 250

• 10

• 50

What is the main advantage of bidirectional search?

• It is less memory intensive

• It can greatly reduce complexity over time

• It is faster than other search strategies

• It always finds the optimal solution

What is the main problem with bidirectional search when there are many objective states?

• It is difficult to do the 'matching' between the two searches

• It is not suitable for large search spaces

• It is not optimal

• It is not possible to generate predecessors

What is the main goal of avoiding repeated states in a search problem?

• To ensure the search is complete

• To minimize the space complexity

• To prevent the search algorithm from getting lost

• To reduce the time complexity

Which problem is not formulated as a search problem in the previous class?

• Towers of Hanoi

• Bucket Filling problem

• Traveling Salesman problem

• Missionaries and Cannibals

What is the main purpose of informed/intelligent/heuristic search?

• To prevent the search algorithm from being lost

• To minimize the time complexity

• To use problem information to guide the search algorithm

• To ensure the search is complete

What is the main difference between Best-First Search and A* Algorithm?

• Best-First Search is always optimal, while A* Algorithm is not

• Best-First Search uses an evaluation function, while A* Algorithm does not

• A* Algorithm is not complete, while Best-First Search is

• A* Algorithm combines greedy with uniform search, while Best-First Search does not

What is the time complexity of Greedy-Search with a good heuristic function?

• O(b^m)

• O(b*m)

• O(b+m)

• O(b^2)

What is the main drawback of Greedy-Search?

• It is not suitable for large search spaces

• It has high space complexity

• It is not complete

• It is not optimal

What is the main advantage of A* Algorithm?

• It minimizes the time complexity

• It is always optimal

• It combines greedy with uniform search

• It is complete