Computer Science: An Overview (12th Edition)
12th Edition
ISBN: 9780133760064
Author: Glenn Brookshear, Dennis Brylow
Publisher: PEARSON
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Chapter 11, Problem 29CRP
Program Plan Intro
Heuristic search:
- It denotes a technique to reach goal state by choosing best promising state.
- It leads to goal state and this search is identified as heuristic search.
- The heuristic values are chosen for each node.
- It denotes that node that has low heuristic value is been chosen over another nodes.
Goal:
- The objective is to find state sequence that would lead to final state.
- The numbers are been ordered from initial state that is unordered and it follows the productions.
- The count of tiles that are out of place denotes heuristic in problem.
- The algorithm is shown below:
- Step 1:
- Construct parent node by taking initial node
- Step 2:
- Check whether the node signifies a final state.
- Step 3:
- If step 2 fails, make child nodes that are possible states and could be attain by moving empty tile in parent nodes.
- Find heuristic value of states.
- Select node that has low heuristic value and move to step 2.
- Step 4:
- If step 2 is true, then algorithm constructed search tree.
- Stop construction of tree further.
- Step 1:
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The Graph Data Structure is made up of nodes and edges. (A Tree Data Structure is a special kind of a
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Question 18
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Chapter 11 Solutions
Computer Science: An Overview (12th Edition)
Ch. 11.1 - Prob. 1QECh. 11.1 - Prob. 2QECh. 11.1 - Prob. 3QECh. 11.1 - Prob. 4QECh. 11.1 - Prob. 5QECh. 11.2 - Prob. 1QECh. 11.2 - Prob. 2QECh. 11.2 - Prob. 3QECh. 11.2 - Prob. 4QECh. 11.2 - Identify the ambiguities involved in translating...
Ch. 11.2 - Prob. 6QECh. 11.2 - Prob. 7QECh. 11.3 - Prob. 1QECh. 11.3 - Prob. 2QECh. 11.3 - Prob. 3QECh. 11.3 - Prob. 4QECh. 11.3 - Prob. 5QECh. 11.3 - Prob. 6QECh. 11.3 - Prob. 7QECh. 11.3 - Prob. 8QECh. 11.3 - Prob. 9QECh. 11.4 - Prob. 1QECh. 11.4 - Prob. 2QECh. 11.4 - Prob. 3QECh. 11.4 - Prob. 4QECh. 11.4 - Prob. 5QECh. 11.5 - Prob. 1QECh. 11.5 - Prob. 2QECh. 11.5 - Prob. 3QECh. 11.5 - Prob. 4QECh. 11.6 - Prob. 1QECh. 11.6 - Prob. 2QECh. 11.6 - Prob. 3QECh. 11.7 - Prob. 1QECh. 11.7 - Prob. 2QECh. 11.7 - Prob. 3QECh. 11 - Prob. 1CRPCh. 11 - Prob. 2CRPCh. 11 - Identify each of the following responses as being...Ch. 11 - Prob. 4CRPCh. 11 - Prob. 5CRPCh. 11 - Prob. 6CRPCh. 11 - Which of the following activities do you expect to...Ch. 11 - Prob. 8CRPCh. 11 - Prob. 9CRPCh. 11 - Prob. 10CRPCh. 11 - Prob. 11CRPCh. 11 - Prob. 12CRPCh. 11 - Prob. 13CRPCh. 11 - Prob. 14CRPCh. 11 - Prob. 15CRPCh. 11 - Prob. 16CRPCh. 11 - Prob. 17CRPCh. 11 - Prob. 18CRPCh. 11 - Give an example in which the closed-world...Ch. 11 - Prob. 20CRPCh. 11 - Prob. 21CRPCh. 11 - Prob. 22CRPCh. 11 - Prob. 23CRPCh. 11 - Prob. 24CRPCh. 11 - Prob. 25CRPCh. 11 - Prob. 26CRPCh. 11 - Prob. 27CRPCh. 11 - Prob. 28CRPCh. 11 - Prob. 29CRPCh. 11 - Prob. 30CRPCh. 11 - Prob. 31CRPCh. 11 - Prob. 32CRPCh. 11 - Prob. 33CRPCh. 11 - What heuristic do you use when searching for a...Ch. 11 - Prob. 35CRPCh. 11 - Prob. 36CRPCh. 11 - Prob. 37CRPCh. 11 - Prob. 38CRPCh. 11 - Suppose your job is to supervise the loading of...Ch. 11 - Prob. 40CRPCh. 11 - Prob. 41CRPCh. 11 - Prob. 42CRPCh. 11 - Prob. 43CRPCh. 11 - Prob. 44CRPCh. 11 - Prob. 45CRPCh. 11 - Prob. 46CRPCh. 11 - Prob. 47CRPCh. 11 - Prob. 48CRPCh. 11 - Draw a diagram similar to Figure 11.5 representing...Ch. 11 - Prob. 50CRPCh. 11 - Prob. 51CRPCh. 11 - Prob. 52CRPCh. 11 - Prob. 53CRPCh. 11 - Prob. 54CRPCh. 11 - Prob. 55CRPCh. 11 - Prob. 56CRPCh. 11 - Prob. 57CRPCh. 11 - Prob. 1SICh. 11 - Prob. 2SICh. 11 - Prob. 3SICh. 11 - Prob. 4SICh. 11 - Prob. 5SICh. 11 - Prob. 6SICh. 11 - Prob. 7SICh. 11 - Prob. 8SICh. 11 - Prob. 9SICh. 11 - Prob. 10SICh. 11 - Prob. 11SICh. 11 - Prob. 12SICh. 11 - A GPS in an automobile provides a friendly voice...Ch. 11 - Prob. 14SI
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- 3. Kleinberg, Jon. Algorithm Design (p. 519, q. 28) Consider this version of the Independent Set Problem. You are given an undirected graph G and an integer k. We will call a set of nodes I "strongly independent" if, for any two nodes v, u € I, the edge (v, u) is not present in G, and neither is there a path of two edges from u to v. That is, there is no node w such that both (v, w) and (u, w) are present. The Strongly Independent Set problem is to decide whether G has a strongly independent set of size at least k. Show that the Strongly Independent Set Problem is NP-Complete.arrow_forwardGiven a graph that is a tree (connected and acyclic). (I) Pick any vertex v.(II) Compute the shortest path from v to every other vertex. Let w be the vertex with the largest shortest path distance.(III) Compute the shortest path from w to every other vertex. Let x be the vertex with the largest shortest path distance. Consider the path p from w to x. Which of the following are truea. p is the longest path in the graphb. p is the shortest path in the graphc. p can be calculated in time linear in the number of edges/verticesarrow_forwardRun BFS algorithm on the following graph starting with vertex s. Whenever there is a choice of vertices, choose the one that is alphabetically first. What is the order that the vertices are visited? What is the shortest path from vertex s to vertex b?arrow_forward
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- 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_forwardThe graph that has been traversed is considered acyclic solely when the Depth-First Search algorithm does not detect any back edges.arrow_forwardA. Use Prim’s algorithm starting at node A to compute the Minimum Spanning Tree (MST) of the following graph. In particular, write down the edges of the MST in the order in which Prim’s algorithm adds them to the MST. Use the format (node1; node2) to denote an edge B. For the same graph as above, write down the edges of the MST in the order in which Kruskal’s algorithm adds them to the MST. NB: Graph in imagearrow_forward
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