Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Expert Solution & Answer
Chapter 4, Problem 5E
Explanation of Solution
Determining the information and using it by the
- See figure S4.1 for the adapted algorithm. For states that OR-SEARCH finds a solution for it records the solution found.
- If it later visits state and the solution is immediately returns by that state.
- The user has to be careful when the OR-SEARCH algorithm fails to find the solution.
- As the user do not allow the cycles, the state can be solved by depending on the path to that solution...
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Students have asked these similar questions
Review the 8-puzzle problem. Consider that the initial state is
1 3 48 27 6 5and the goal state is1 2 38 47 6 5Apply the breath-first-search method to obtain the path from the initial state to the goal state. Youneed to show the corresponding search tree. As soon as you find the goal state, you can stop the searchprocess.
Given the following search tree, state the order in which the nodes will be searched for breadth first and depth first, until a solution B is reached.
Let G be an undirected graph whose vertices are the integers 1 through 8, and let the adjacent vertices of each vertex be given by the table below:
look at the picture sent
Assume that, in a traversal of G, the adjacent vertices of a given vertex are returned in the same order as they are listed in the table above.
Which statement of the following is correct?
group of answer choices
a) The sequence of vertices visited using a DFS traversal starting at vertex 1: 1, 2, 3, 4, 6, 5, 7, 8.
b) The sequence of vertices visited using a BFS traversal starting at vertex 1: 1, 2, 3, 4, 6, 5, 7, 8.
c) Both sequences are wrong.
d) Both sequences are correct.
Chapter 4 Solutions
Artificial Intelligence: A Modern Approach
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- In hill-climbing algorithms there are steps that make lots of progress and steps that make very little progress. For example, the first iteration on the input given might find a path through the augmentation graph through which a flow of 30 can be added. It might, however, find the path through which only a flow of 2 can be added. How bad might the running time be when the computation is unlucky enough to always take the worst legal step allowed by the algorithm? Start by taking the step that increases the flow by 2 for the input. Then continue to take the worst possible step. You could draw out each and every step, but it is better to use this opportunity to use loop invariants. What does the flow look like after i iterations? Repeat this process on the same graph except that the four edges forming the square now have capacities 1,000,000,000,000,000 and the crossover edge has capacity 1. (Also move t to c or give that last edge a large capacity.)1. What is the worst case number of…arrow_forwardQuestion 1: In graph theory, a graph X is a "complement" of a graph F if which of the following is true? Select one: a. If X is isomorph to F, then X is a complement of F. b. If X has half of the vertices of F (or if F has half of the vertices of X) then X is a complement of F. c. If X has the same vertex set as F, and as its edges ONLY all possible edges NOT contained in F, then X is a complement of F. d. If X is NOT isomorph to F, then X is a complement of F. Question 2: Which statement is NOT true about Merge Sort Algorithm: Select one: a. Merge Sort time complexity for worst case scenarios is: O(n log n) b. Merge Sort is a quadratic sorting algorithm c. Merge Sort key disadvantage is space overhead as compared to Bubble Sort, Selection Sort and Insertion Sort. d. Merge Sort adopts recursive approacharrow_forwardPlease provide all rounds of Dijkstra algorithm execution. for your own graph example.and also write a code for your own example and also you need to define the function that actually prints the shortest patharrow_forward
- Vertex S denotes the start state and vertices G1 and G2 denote the two goal states. Directed edges are labelled with the actual costs of traversing the edge. In what order would Breadth-First Search retrieve the states from the frontier when starting the search in S? If all else is equal, consider states in alphabetic order. There are two possible correct answers, depending on what variant of Breadth-First Search you are using. Select either one of them to receive full marks. options are S, A, B, C, D, E, F, G1 b. S, A, B, C, E, F, D, G1 c. S, A, B, C, E, F, G1 d. S, A, B, C e. S, A, C, G1 f. S, A, E, G1 g. S, B, A, C, E h. S, B, F, D, G2 i. S, C, B, F, A, D, E, G1 j. S, C, G1arrow_forwardR-13.6 - Suppose we represent a graph G having n vertices and m edges with the edge list structure. Why, in this case, does the insertVertex function run in O(1) time while the eraseVertex function runs in O(m) time?arrow_forwardThe diagram below shows a search space in which the initial state is List the states in the order in which they would be explored in a depth-first search Given that the goal state is H, show the current state, and open and closed lists, at each iteration of a breadth-first search to locate the goal state. State the main advantage of breadth-first search and give the reason for this advantage. List the states in the order in which they would be explored in a iterative deepening search.arrow_forward
- Based on the given adjacency lists and the figure below for the graph search, which of the following statements are correct? (Select all that applies.) adj(s) = [a, c, d], adj(a) = [ ], adj(c) = [e, b], adj(b) = [d], adj(d) = [c], adj(e) = [s]. see the picture sent Group of answer choices Breadth-First Search: s a c d e b Breadth-First Search: s a c d b e Depth-First Search: s a c b d e Depth-First Search: s a c e b darrow_forwardVertex S denotes the start state and vertices G1 and G2 denote the two goal states. Directed edges are labelled with the actual costs of traversing the edge. In what order would Depth-First Search visit the states when starting the search in S? Consider the sequence of states as they are encountered for the first time on each path. Remember that DFS forgets that a state has been visited when backtracking over it. If all else is equal, consider states in alphabetic order. options are : a. S, A, B, C, D, E, F, G1 b. S, A, B, C, E, F, D, G1 c. S, A, B, C, E, F, G1 d. S, A, B, C, G1 e. S, A, C, G1 f. S, A, E, G1 g. S, B, A, C, E, G1 h. S, B, F, D, G2 i. S, C, B, F, A, D, E, G1 j. S, C, G1arrow_forwardUsing A* Search, show the process of identifying the correct path from the start node (A) to end node (M). Heuristic Values State Value A 0 B 3 C 6 D 5 E 1 F 3 G 2 H 4 I 3 J 2 K 1 L 2 M 1arrow_forward
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