- What is the fringe in the context of search algorithms?
In English, the fringe is (also) defined as the outer, marginal, or extreme part of an area, group, or sphere of activity In the context of AI search algorithms, the state (or search) space is usually represented as a graph, where nodes are states and the edges are the connections (or actions) between the corresponding states
- A* and uniform-cost search are apparently incomplete
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- Why is A* optimal if the heuristic function is admissible?
The tree search does not remember which states it has already visited, only the "fringe" of states it hasn't visited yet A graph search is a general search strategy for searching graph-structured problems, where it's possible to double back to an earlier state, like in chess (e g both players can just move their kings back and forth)
- Why do we use a last-in-first-out queue in depth-first search?
We use the LIFO queue, i e stack, for implementation of the depth-first search algorithm because depth-first search always expands the deepest node in the current frontier of the search tree
- How does the uniform-cost search algorithm work?
Uniform Cost Search is also called the Cheapest First Search For an example and entire explanation you can directly go to this link: Udacity - Uniform Cost Search
- What is the space complexity of breadth-first search?
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- norvig russell - What does the statement with the max do in the . . .
By taking the max, the code ensures that states that are restored maintain at least the cost of the previously best unexpanded state (If the g+h cost is larger, then we know the state wasn't previously expanded and it wasn't previously the state on the fringe with the minimum edge cost )
- How is iterative deepening A* better than A*?
The iterative deepening A* search is an algorithm that can find the shortest path between a designated start node and any member of a set of goals The A* algorithm evaluates nodes by combining the
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