24 Questions
What is the main difference between uninformed search algorithms and informed search algorithms?
Informed search algorithms use problem-specific knowledge, while uninformed search algorithms do not.
Heuristic functions are used in uninformed search algorithms to guide the search process.
False
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.
g(n), h(n)
Which search algorithm orders the nodes in the frontier by the evaluation function f(n) = g(n) + h(n)?
A* Search
Match the following search algorithms with their characteristics:
Best-First Search = A* Search Orders nodes by an evaluation function = Orders nodes by f(n) = g(n) + h(n)
Tree search is more efficient than graph search when the state space has cycles or repeated states.
False
Why is the quality of the heuristic function important in informed search algorithms?
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.
Which of the following is a characteristic of Greedy Best-First Search?
It 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.
True
What is the main difference between Tree Search and Graph Search?
Graph search keeps track of visited states to avoid revisiting and to handle cycles, while Tree Search does not.
The heuristic function used in Greedy Search is an estimate of the ______________________________ from the current state to the goal state.
distance
Match the following search algorithms with their characteristics:
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
What is the purpose of the priority queue in search algorithms?
To determine the order of node expansion
Greedy Search is a type of informed search.
True
What is the problem with using Tree Search in search problems with complex graphs?
It may become stuck in a loop if it revisits the same state
In Greedy Search, the ______________________________ is used to guide the search towards the goal state.
heuristic function
Which of the following search algorithms is most suitable for search problems with complex graphs, including cycles and shared states?
Graph Search
What is the primary purpose of a heuristic function in informed search?
To estimate the cost to reach the goal from a given state
A heuristic function is admissible if it always overestimates the true cost to reach the goal.
False
What is the difference between a tree search and a graph search in A* algorithm?
Tree search is used when the graph has no cycles, while graph search is used when the graph has cycles.
The evaluation function f(n) in A* search is equal to g(n) + ______________.
h(n)
What is the main difference between A* search and Uniform-Cost Search (UCS)?
A* search uses a heuristic function, while UCS does not
Match the following search strategies with their characteristics:
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
Study Notes
Informed Search
- 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 noden. - Evaluation function
f(n) = g(n) + h(n)provides an estimate of the total cost to the goal through noden. - "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
nand every successorn'ofn, the estimated cost of reaching the goal fromnis no greater than the cost of getting ton'plus the estimated cost of reaching the goal fromn'.
Search Efficiency
- Search efficiency depends heavily on heuristic quality.
- The better the heuristic, the faster the search.
Tree Search vs Graph 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
- 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).
This quiz covers the concept of Greedy Best-First Search algorithm, its advantages and limitations, and how it handles complex graphs with cycles and shared states.
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