Greedy Best-First Search Algorithm

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Questions and Answers

What is the main difference between uninformed search algorithms and informed search algorithms?

  • Informed search algorithms are more complex than uninformed search algorithms.
  • Informed search algorithms use problem-specific knowledge, while uninformed search algorithms do not. (correct)
  • Uninformed search algorithms use problem-specific knowledge, while informed search algorithms do not.
  • Uninformed search algorithms are more efficient than informed search algorithms.

Heuristic functions are used in uninformed search algorithms to guide the search process.

False (B)

What is the purpose of the heuristic function h(n) in informed search algorithms?

The heuristic function h(n) estimates the optimal cost to the goal from node n.

The evaluation function f(n) = ___________ + ___________ , where g(n) is the known path cost so far to node n and h(n) is the estimate of the optimal cost to the goal from node n.

<p>g(n), h(n)</p> Signup and view all the answers

Which search algorithm orders the nodes in the frontier by the evaluation function f(n) = g(n) + h(n)?

<p>A* Search (D)</p> Signup and view all the answers

Match the following search algorithms with their characteristics:

<p>Best-First Search = A* Search Orders nodes by an evaluation function = Orders nodes by f(n) = g(n) + h(n)</p> Signup and view all the answers

Tree search is more efficient than graph search when the state space has cycles or repeated states.

<p>False (B)</p> Signup and view all the answers

Why is the quality of the heuristic function important in informed search algorithms?

<p>The quality of the heuristic function is important because it affects the search efficiency, and a better heuristic function can lead to a faster search.</p> Signup and view all the answers

Which of the following is a characteristic of Greedy Best-First Search?

<p>It uses an estimate of the distance from the current state to the goal state. (B)</p> Signup and view all the answers

Tree search may become stuck in a loop if it revisits the same state.

<p>True (A)</p> Signup and view all the answers

What is the main difference between Tree Search and Graph Search?

<p>Graph search keeps track of visited states to avoid revisiting and to handle cycles, while Tree Search does not.</p> Signup and view all the answers

The heuristic function used in Greedy Search is an estimate of the ______________________________ from the current state to the goal state.

<p>distance</p> Signup and view all the answers

Match the following search algorithms with their characteristics:

<p>A* Search = Uses an estimate of the total cost from the start state to the goal state Best-First Search = Uses an estimate of the distance from the current state to the goal state Greedy Search = Uses an estimate of the distance from the current state to the goal state Tree Search = May become stuck in a loop if it revisits the same state</p> Signup and view all the answers

What is the purpose of the priority queue in search algorithms?

<p>To determine the order of node expansion (A)</p> Signup and view all the answers

Greedy Search is a type of informed search.

<p>True (A)</p> Signup and view all the answers

What is the problem with using Tree Search in search problems with complex graphs?

<p>It may become stuck in a loop if it revisits the same state</p> Signup and view all the answers

In Greedy Search, the ______________________________ is used to guide the search towards the goal state.

<p>heuristic function</p> Signup and view all the answers

Which of the following search algorithms is most suitable for search problems with complex graphs, including cycles and shared states?

<p>Graph Search (C)</p> Signup and view all the answers

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

<p>To estimate the cost to reach the goal from a given state (D)</p> Signup and view all the answers

A heuristic function is admissible if it always overestimates the true cost to reach the goal.

<p>False (B)</p> Signup and view all the answers

What is the difference between a tree search and a graph search in A* algorithm?

<p>Tree search is used when the graph has no cycles, while graph search is used when the graph has cycles.</p> Signup and view all the answers

The evaluation function f(n) in A* search is equal to g(n) + ______________.

<p>h(n)</p> Signup and view all the answers

What is the main difference between A* search and Uniform-Cost Search (UCS)?

<p>A* search uses a heuristic function, while UCS does not (A)</p> Signup and view all the answers

Match the following search strategies with their characteristics:

<p>Greedy Search = Always chooses the path that looks best at the moment Best-First Search = Always chooses the path that looks best at the moment A* Search = Combines cost so far with a heuristic function to guide the search</p> Signup and view all the answers

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Study Notes

  • Informed search algorithms use problem-specific knowledge (heuristics) to guide the search process towards the goal more effectively.
  • Heuristic values are determined through a collaborative effort involving domain experts, algorithm designers, data scientists, and software engineers.
  • Heuristic function h(n) estimates the optimal cost to the goal from node n.
  • Evaluation function f(n) = g(n) + h(n) provides an estimate of the total cost to the goal through node n.
  • "Best-first" search implementation orders nodes in the frontier by an evaluation function.
  • Greedy Best-First search orders nodes by h(n).
  • A* search orders nodes by f(n).

Heuristic Function

  • A heuristic function is an estimate of the cost to reach the goal from a given state.
  • Admissibility: a heuristic is admissible if it never overestimates the true cost to reach the goal.
  • Consistency (Monotonicity): a heuristic is consistent if, for every node n and every successor n' of n, the estimated cost of reaching the goal from n is no greater than the cost of getting to n' plus the estimated cost of reaching the goal from n'.

Search Efficiency

  • Search efficiency depends heavily on heuristic quality.
  • The better the heuristic, the faster the search.
  • Tree search treats the search space as a tree structure, where each state is represented by a unique node, and nodes do not share children.
  • Graph search treats the search space as a graph, where nodes can have multiple parents and can be revisited.
  • Graph search is suitable for search problems with complex graphs, including cycles and shared states.
  • A* search is an optimal search algorithm that uses an admissible and consistent heuristic function.
  • A* search avoids expanding paths that are already expensive.
  • A* search always terminates with a solution path.
  • A* algorithm is identical to UCS except that the priority queue sort function is f(n) = g(n) + h(n).

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