Although shortest paths algorithms (e.g. Dijkstra's, A*) and minimum spanning tree algorithms (e.g. Prim's, Kruskal's) a

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Although Shortest Paths Algorithms E G Dijkstra S A And Minimum Spanning Tree Algorithms E G Prim S Kruskal S A 1 (130.23 KiB) Viewed 33 times

Although shortest paths algorithms (e.g. Dijkstra's, A*) and minimum spanning tree algorithms (e.g. Prim's, Kruskal's) are both run on graphs, they have differing end goals. True False For any graph with all unique edge weights, the shortest path tree from any start vertex and the minimum spanning tree will always be the same. O True O False A* search is guaranteed to be at least as efficient as Dijkstra's, regardless of the heuristic used. Here, efficiency is defined as visiting as few nodes as possible. True O False Dijkstra's algorithm will correctly generate a Shortest Paths Tree for any graph with negative edge weights. True O False Adding some positive constant k to every edge in a graph with positive edge weights will not change the shortest Paths Tree that Dijkstra's algorithm generates. O True O False Multiplying every edge in a graph with positive edge weights by some positive constant k will not change the shortest Paths Tree that Dijkstra's algorithm generates. O True False Given any graph with distinct edge weights and any node in the graph as your starting node, there is only one possible Shortest Paths Tree that you can generate. O True O False