Podcast
Questions and Answers
What data structure is used to store the list in Breadth First Search?
What data structure is used to store the list in Breadth First Search?
- Heap
- Stack
- Linked List
- Queue (correct)
Which search technique guarantees to find a solution and keeps every node in memory?
Which search technique guarantees to find a solution and keeps every node in memory?
- Breadth First Search (correct)
- Uniform Cost Search
- A* Search
- Depth-First Search
What property must hold true for every node in Uniform Cost Search to find the cheapest solution?
What property must hold true for every node in Uniform Cost Search to find the cheapest solution?
- $g(successor(n)) < g(n)$
- $g(successor(n)) \geq g(n)$ (correct)
- $g(successor(n)) > g(n)$
- $g(successor(n)) = g(n)$
Which search algorithm ensures the shortest path to the goal in terms of cost?
Which search algorithm ensures the shortest path to the goal in terms of cost?
Which search algorithm expands one of the nodes at the deepest level of the tree?
Which search algorithm expands one of the nodes at the deepest level of the tree?
What is the evaluation function used in A* search algorithm?
What is the evaluation function used in A* search algorithm?
In A* search, what does the function g(n) represent?
In A* search, what does the function g(n) represent?
In which search technique are successors put at the end of a queue for expansion?
In which search technique are successors put at the end of a queue for expansion?
Which property of A* search ensures that it guarantees reaching the goal state?
Which property of A* search ensures that it guarantees reaching the goal state?
What is the worst-case time and space complexity of heuristic algorithms like A* search?
What is the worst-case time and space complexity of heuristic algorithms like A* search?
Based on its properties, is A* search algorithm optimal?
Based on its properties, is A* search algorithm optimal?
Which memory-related issue arises when using A* search algorithm?
Which memory-related issue arises when using A* search algorithm?
What data structure can be used to implement Depth-first search?
What data structure can be used to implement Depth-first search?
Which type of spaces does Depth-first search fail in?
Which type of spaces does Depth-first search fail in?
What would improve search efficiency greatly according to the text?
What would improve search efficiency greatly according to the text?
What does the heuristic function h(n) estimate in A* search?
What does the heuristic function h(n) estimate in A* search?
How does A* search differ from Best First Search?
How does A* search differ from Best First Search?
What property makes Depth-first search incomplete and not optimal?
What property makes Depth-first search incomplete and not optimal?
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Study Notes
Search Strategies
- Informed search strategies use domain knowledge to order choices and explore the most promising paths first.
- Best First Search:
- Uses a heuristic function, h(n), to estimate the goodness of a node.
- Estimates the cost of the path from the current state to a goal state.
- Expands all nodes on a given level of the search tree before moving to the next level.
- Implemented using a queue data structure.
- Properties: takes space, optimal, and complete.
- Uniform Cost Search:
- Modifies Best First Search to find the shortest path to the goal in terms of cost.
- Expands the least-cost unexpanded node.
- Implemented using a priority queue ordered by path cost.
- Properties: finds the cheapest solution, takes space, and has a cost that never decreases along the path.
Depth-First Search
- Expands one of the nodes at the deepest level of the tree.
- Implemented using a stack data structure.
- Properties: incomplete, not optimal, fails in infinite depth spaces, and spaces with loops.
A* Search Algorithm
- Considers both the estimated cost of getting from the current node to the goal node (h(n)) and the cost of getting from the initial node to the current node (g(n)).
- Evaluation function: f(n) = h(n) + g(n).
- Implemented by expanding the node with the lowest evaluation function.
- Properties: complete, optimal, and optimally efficient for any given admissible heuristic function.
- Takes memory and has exponential time and space complexity in the worst case.
- The quality of the heuristic function affects the time and space complexity.
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