Concept explainers
Heuristic system:
The heuristic system considers all the immediate possible conditions that may lead to a solution for the problem. The system proceeds in the same manner until all the possible conditions are achieved. The heuristic system may require a large amount of work but ultimately it approaches towards a solution. The solution is one of the conditions achieved at the last. The conditions achieved at last may be in large numbers. It guarantees to have a solution among many conditions achieved in the end.
Best fit
To eliminate irrelevant moves, the tiles that are out of place should always be adjacent to the hole. The tiles that are already in place should not be moved. The best fit algorithm eliminates the moves having a higher cost, but only for proceeding moves. This algorithm does not consider the overall cost associated with a path.
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Computer Science: An Overview (12th Edition)
- For straight-line distance heuristic, draw the search tree after expansion of each node until the termination of the algorithm for: a) Greedy best-first search (label all node with their h values). What is the solution (list of visited cities) found by the algorithm? b) A* search (label all nodes with their f values). What is the solution (list of visited cities) found by the algorithm?arrow_forwardImplement RBFS algorithm and draw the search tree for the following search space. (Assume start state S and goal state G) 150 42 B H 6 2 66 105 A G 10 7 10 E 30 36 100 1 63 1. 2.arrow_forwardYour second function is called “isTree". Its input is a graph G, which is a dictionary whose keys are the vertices, and whose values are lists of vertices that are adjacent to the given vertex. Its output is True if G is a tree and False if G is not a tree. Hint: You may want to make use of your "connected" function from the last coding assignment.arrow_forward
- Question.arrow_forwardTrue or false: For graphs with negative weights, one workaround to be able to use Dijkstra’s algorithm (instead of Bellman-Ford) would be to simply make all edge weights positive; for example, if the most negative weight in a graph is -8, then we can simply add +8 to all weights, compute the shortest path, then decrease all weights by -8 to return to the original graph. Select one: True Falsearrow_forwardNote: Your solution should have O(n) time complexity, where n is the number of elements in l, and O(1) additional space complexity, since this is what you would be asked to accomplish in an interview. Given a linked list l, reverse its nodes k at a time and return the modified list. k is a positive integer that is less than or equal to the length of l. If the number of nodes in the linked list is not a multiple of k, then the nodes that are left out at the end should remain as-is. You may not alter the values in the nodes - only the nodes themselves can be changed.arrow_forward
- f). True or False. Prim's algorithm will work with negative edge weights. True False g). True or False. It's impossible for the MST of a graph to contain the largest weighted edge. True False h). True or False. The Shortest Paths Tree returned by Dijkstra's will never be a correct MST. True False i). True or False. A graph with unique edge weights will have exactly one MST. You might find it useful to know that Kruskal's algorithm can generate any MST depending on its tie-breaking scheme. True False j). True or False. A graph with non unique edge weights will always have a non unique MST True False k). True or False. If you take any graph G with positive edge weights and square all the edge weights and turn it into the graph G', G and G' have all the same MST's True False I). True or False. The minimum weight edge of any cycle in a graph G will be part of any MST of G True Falsearrow_forward..... ..arrow_forwardF Find the traversal order of the nodes using DFS (Depth First Search) and BFS (Breadth-First Search) starting from node A. In each step, the selection of the next node to be visited is according to the alphabetical order (from smallest to highest) when there are several alternatives. Fill each blank area below with just one letter. DFS: I For Bank 1 BFS:arrow_forward
- 1. In the figure bellow, the nodes are laid out on a grid where each square has a size of 5x5 units. The node P is the start node, and the D node is goal node. List the order of nodes in which the A* algorithm explores the graph. Use the Manhattan Distances as a heuristic function. Note that if two nodes have the same value, select the nodes in alphabetical order. 31 33 24 31 25 40 21 22 25 25 21 start 13 35 35 45 21 Figure: graph with edge costs (zarrow_forwardb3arrow_forwardNo hand written and fast answer with explanationarrow_forward
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