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Algorithms Graph Search - Stanford Computer Science

Graph Search AlgorithmsSteve Mussmann and Abi SeeShortest Path ProblemsFind the shortest path from source to targetApplications: RoboticsCommercialSearch & RescueDomesticApplications: Route-PlanningApplications: Game-playingTic-tac-toeGoGraphs have nodes and many nodes are there?How many edges?GraphsGraphsWe cast real-world problems as can be undirected or can have to represent grids as graphs?Each cell is a node. Edges connect adjacent have no edgesHow to represent grids as graphs? Graph TraversalAlgorithmsGraph Traversal Algorithms These Algorithms specify an order to Search through the nodes of a Graph . We start at the source node and keep searching until we find the target node. The frontier contains nodes that we've seen but haven't explored yet. Each iteration, we take a node off the frontier, and add its neighbors to the First Search DFS uses "last in first out".This is a First Search vs. Depth First SearchBFS uses "first in first out".

Now in the Computer History Museum! A* Search A* Search combines the strengths of Breadth First Search and Greedy Best First. Like BFS, it finds the shortest path, and like Greedy Best First, it's fast. Each iteration, A* chooses the node on the frontier which minimizes:

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