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Consider the 8-puzzle below with initial and goal states shown, where 0 corresponds to an empty space and the other numbers correspond to number tiles. The number tiles can move left, right, up, or down into the empty space (where available). The neighborhood operator consists of applying a possible move to the current state. Using hill climbing search algorithm and Manhattan distance (see Note below) as the objective, show the first two moves of hill climbing algorithm starting from the initial state while showing all the nodes generated at each step and their corresponding objective value. Note: In a 2D plane with point p₁ at coordinates (x₁, y₁) and point Pp2 at coordinates (x2, y2), the Manhattan distance between points p₁ and p₂ is computed as Ix₁-x₂|+ ly₁-Y₂l where ly₁-Yal represents absolute difference between y₁ and y₁. As an example of coordinates, tile 8 in start state below can be considered at coordinates (1,2) while tile 8 in goal state below can be considered at coordinates (2,3). Start state: 8 7 2 0 5 3 4 6 Goal state: 1 2 3 5 6 780 4

Consider the 8-puzzle below with initial and goal states shown, where 0 corresponds to an empty space and the other numbers correspond to number tiles. The number tiles can move left, right, up, or down into the empty space (where available). The neighborhood operator consists of applying a possible move to the current state. Using hill climbing search algorithm and Manhattan distance (see Note below) as the objective, show the first two moves of hill climbing algorithm starting from the initial state while showing all the nodes generated at each step and their corresponding objective value. Note: In a 2D plane with point p₁ at coordinates (x₁, y₁) and point Pp2 at coordinates (x2, y2), the Manhattan distance between points p₁ and p₂ is computed as Ix₁-x₂|+ ly₁-Y₂l where ly₁-Yal represents absolute difference between y₁ and y₁. As an example of coordinates, tile 8 in start state below can be considered at coordinates (1,2) while tile 8 in goal state below can be considered at coordinates (2,3). Start state: 8 7 2 0 5 3 4 6 Goal state: 1 2 3 5 6 780 4

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Consider the 8-puzzle below with initial and goal states shown, where O corresponds to an empty space and the other numbers correspond to number tiles. The number tiles can move left, right, up, or down into the empty space (where available). The neighborhood operator consists of applying a possible move to the current state. Using hill climbing search algorithm and Manhattan distance (see Note below) as the objective, show the first two moves of hill climbing algorithm starting from the initial state while showing all the nodes generated at each step and their corresponding objective value. Note: In a 2D plane with point pi at coordinates (x, yı) and point p, at coordinates (x2, ya), the Manhattan distance between points pi and pa is computed as |x1 - Xa| + lyı - Y2l where ly: - Val represents absolute difference between y, and y. As an example of coordinates, tile 8 in start state below can be considered at coordinates (1,2) while tile 8 in goal state below can be considered at coordinates (2,3). Goal state: Start state: 12 3 4 56 8. 7 80 7. MXIX X ixIx nix ix XI x nx nX MX x ix niX ix X ririrk kix ixix wYi Xix x x x XIx riririex rir 3. 6. 5. 1.
Transcribed Image Text:Consider the 8-puzzle below with initial and goal states shown, where O corresponds to an empty space and the other numbers correspond to number tiles. The number tiles can move left, right, up, or down into the empty space (where available). The neighborhood operator consists of applying a possible move to the current state. Using hill climbing search algorithm and Manhattan distance (see Note below) as the objective, show the first two moves of hill climbing algorithm starting from the initial state while showing all the nodes generated at each step and their corresponding objective value. Note: In a 2D plane with point pi at coordinates (x, yı) and point p, at coordinates (x2, ya), the Manhattan distance between points pi and pa is computed as |x1 - Xa| + lyı - Y2l where ly: - Val represents absolute difference between y, and y. As an example of coordinates, tile 8 in start state below can be considered at coordinates (1,2) while tile 8 in goal state below can be considered at coordinates (2,3). Goal state: Start state: 12 3 4 56 8. 7 80 7. MXIX X ixIx nix ix XI x nx nX MX x ix niX ix X ririrk kix ixix wYi Xix x x x XIx riririex rir 3. 6. 5. 1.
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