Informed Search Quiz extra

What is the purpose of defining a heuristic function in informed search?

• To skip certain nodes during the search

• To increase the complexity of the search algorithm

• To generate random values for each node

• To estimate the cost of the minimal path from the current node to the goal state

What are the characteristics of heuristic functions used in informed search?

• Dynamic, Positive, Domain-independent

• Random, Zero, Task-specific

• Fixed, Negative, General-purpose

• Arbitrary, Non-negative, Problem-specific

In the 8-puzzle problem, what does the Manhattan Distance heuristic measure?

• The sum of distances each tile is from its goal position

• The number of misplaced tiles

• The total number of moves required to solve the puzzle

• The randomness of the tile positions

What is the evaluation function used in Greedy Best First Search?

• f(n) = h(n)

• f(n) = g(n) + h(n)

• f(n) = g(n) - h(n)

• f(n) = g(n) * h(n)

What does the A* algorithm aim to minimize?

• The total estimated solution cost

• The randomness in selecting nodes

• The number of nodes expanded

• The depth of the search tree

When is a heuristic considered admissible in the A* algorithm?

• When h(n) > h*(n) holds

• When h(n) <= h*(n) holds

• When h(n) = h*(n)

• When h(n) is a negative value

What is the primary advantage of using the A* algorithm in search problems?

• Reduces the memory usage of the search algorithm

• Guarantees finding an optimal solution

• Increases the number of explored nodes

• Guarantees finding a solution quickly

What is the heuristic function used in the 8-puzzle problem with A* algorithm?

• f(n) = h(n)

• f(n) = g(n) + h(n)

• h(n) = estimated cost of the cheapest solution through n

• h*(n)= true cost of the minimal cost path from n to a goal

What is the primary difference between Greedy Best First Search and A* algorithm?

• Greedy expands nodes based on the evaluation function f(n), while A* does not

• A* selects nodes based on the closest to the goal, while Greedy does not

• Greedy guarantees finding an optimal solution, while A* does not

• A* incorporates the cost from the start state to the current node, while Greedy does not

What is the role of heuristics in guiding search algorithms?

• To provide domain-specific information to select the best path

• To introduce randomness in the search process

• To increase the search space exponentially

• To skip nodes with high heuristic values