Informed Search Quiz

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

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

• To skip certain nodes during the search

• To generate random values for each node

• To increase the complexity of the search algorithm

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

• Fixed, Negative, General-purpose

• Arbitrary, Non-negative, Problem-specific

• Dynamic, Positive, Domain-independent

• Random, Zero, Task-specific

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

• The number of misplaced tiles

• The number of moves made so far

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

• The total number of tiles in the puzzle

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)

• f(n) = h*(n)

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

• Selecting nodes randomly

• Ignoring heuristic information

• Maximizing the number of nodes expanded

• Minimizing the total estimated solution cost

What does the h(n) term represent in the A* algorithm?

• The cost to get to the goal from node n

• The estimated cost of the cheapest solution through n

• The true cost of the minimal cost path from n to a goal

• The minimal-cost path from the start state to state n

What does an admissible heuristic guarantee in the A* algorithm?

• The heuristic function will be ignored

• The algorithm will always find the shortest path

• The search will be faster

• The first solution found will be an optimal one

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

• A* incorporates a breadth-first component in the evaluation function

• Greedy Best First Search always finds the optimal solution

• A* is not complete

• Greedy Best First Search is admissible

What is the heuristic value for the 8-puzzle problem when h(n) = 0?

• n is a goal node

• n is a dead-end that can never lead to a goal

• n is misplaced

• n is the starting node

What is the heuristic function used in Recursive Best First Search?

• f(n) = h(n)

• f(n) = g(n) + h(n)

• f(n) = g(n)

• f(n) = h*(n)