Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Question
Chapter 3, Problem 21E
Program Plan Intro
Breadth-first search:
- Breadth First Search (BFS), is the
algorithm that traverses or searches tree or graph data structures. - The search starts with the tree root, and then explores all the neighbor nodes at the present depth before moving to the nodes at the next depth level.
- The strategy used in this is quite opposite to depth-first search.
Depth First Search:
- Depth First Search (DFS), is the algorithm to traverse or search tree or graph data structures.
- The search starts with the root node, and then explores as far as possible along each branch before backtracking.
Uniform Cost Search:
- Uniform Cost Search (UCS) is the algorithm known to best for a search problem, and this does not include the use of heuristics.
- It solves any general graph for an optimal cost.
- Uniform cost search searches the branches which are more or less the same in cost.
Expert Solution & Answer
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Exercise d. Coloring, with the oracle's help. (Textbook problem 4.2)
Analogous to the previous problem, but a little trickier: suppose we have an oracle for
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Chapter 3 Solutions
Artificial Intelligence: A Modern Approach
Ch. 3 - Explain why problem formulation must follow goal...Ch. 3 - Prob. 2ECh. 3 - Prob. 3ECh. 3 - Prob. 4ECh. 3 - Prob. 5ECh. 3 - Prob. 6ECh. 3 - Prob. 8ECh. 3 - Prob. 9ECh. 3 - Prob. 10ECh. 3 - Prob. 11E
Ch. 3 - Prob. 12ECh. 3 - Prob. 13ECh. 3 - Prob. 14ECh. 3 - Prob. 15ECh. 3 - Prob. 16ECh. 3 - Prob. 17ECh. 3 - Prob. 18ECh. 3 - Prob. 20ECh. 3 - Prob. 21ECh. 3 - Prob. 22ECh. 3 - Trace the operation of A search applied to the...Ch. 3 - Prob. 24ECh. 3 - Prob. 25ECh. 3 - Prob. 26ECh. 3 - Prob. 27ECh. 3 - Prob. 28ECh. 3 - Prob. 29ECh. 3 - Prob. 31ECh. 3 - Prob. 32E
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Similar questions
- 5. (This question goes slightly beyond what was covered in the lectures, but you can solve it by combining algorithms that we have described.) A directed graph is said to be strongly connected if every vertex is reachable from every other vertex; i.e., for every pair of vertices u, v, there is a directed path from u to v and a directed path from v to u. A strong component of a graph is then a maximal subgraph that is strongly connected. That is all vertices in a strong component can reach each other, and any other vertex in the directed graph either cannot reach the strong component or cannot be reached from the component. (Note that we are considering directed graphs, so for a pair of vertices u and v there could be a path from u to v, but no path path from v back to u; in that case, u and v are not in the same strong component, even though they are connected by a path in one direction.) Given a vertex v in a directed graph D, design an algorithm for com- puting the strong connected…arrow_forwardDo some outside research on depth-first traversal as it relates to traversing graphs. Then answer the following questions: a. Suppose you have an arbitrary connected graph G, shown in the image below. Use the vertex A as your starting point. Write out the order in which the algorithm could traverse the graph with a depth-first search, and explain your reasoning (there are multiple correct answers, hence the need for an explanation). b. Use a proof by induction to prove that when a depth-first traversal is performed, every vertex v in your graph G will have been visited at least one time. B D H E A G с I FLarrow_forwardQuestion 8 Greedy best-fırst search is equivalent to A* search with all step costs set to 0. O True O False Question 9 If you had implemented Uniform Cost Search (the graph search version) in Programming Assignment 1, it would have found an optimal solution. (You may assume that the path costs are kept with the nodes on the frontier and explored lists and checked when comparing newly generated states to what has been seen before.) O True O False Question 10 A* search with an admissible heuristic always expands fewer nodes than depth-first search. O True O Falsearrow_forward
- Depth-first search always expands at least as many nodes as A∗ search with an admissible heuristic. True or false? Explain your answers in one sentencearrow_forward(c) Consider a sort of items, according to their keys, that inserts all the items one at a time into an initially empty regular binary search tree and then applies an in-order traversal to complete the sort. Assume that all items have distinct keys. Using big-Theta notation.what is the worst-case complexity of the sort? What is the average-case complexity of the sort? Now answer the same two questions if an AVL tree is used instead of a regular binary search tree.arrow_forwardConsider a graph and implement Breadth-first search, Uniform-cost search, Depth-first search, Depth-limited search, Iterative deepening depth-first search and Bidirectional search using your favorite programming language. Also draw and visualize the solution.arrow_forward
- Which of the statements are correct? (Select all that applies.) Group of answer choices A digraph is a graph whose edges are all directed. Digraphs can be applicable for detecting wash trade in financial market. Dijkstra's algorithm is based on the greedy method. Kruskal algorithm can be used to create a Minimum Spanning Tree. BFS runs in O(V+E) , where V is the number of vertices and E is the number of edges in the graph. DFS runs in O(V+E) as well.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_forwardDo the graph of each traversal DFS and BFSarrow_forward
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