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1 3 4 8 6 2 7 5 2 8 1 2 8 1 4 4 3 4 6 3 76 5 7 5 Implement the following search algorithms and test them on the start sta state shown above. Only A* needs to detect duplicate states and eliminate the remainder of the search.

1 3 4 8 6 2 7 5 2 8 1 2 8 1 4 4 3 4 6 3 76 5 7 5 Implement the following search algorithms and test them on the start sta state shown above. Only A* needs to detect duplicate states and eliminate the remainder of the search.

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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Artificial Intelligence programming assignment Here is the goal state and four start states for the 8-puzzle. Goal: Easy: Medium: Hard: Worst: 1 2 3 5 6 7 1 3 4 8 6 2 2 8 1 2 8 1 8 4 4 3 4 6 3 4 8. 76 5 7 7 6 5 7 5 3 2 1 Implement the following search algorithms and test them on the start states and goal state shown above. Only A* needs to detect duplicate states and eliminate them from the remainder of the search. 1. A* search using the heuristic function f*(n) = g(n) + h*(n), where h*(n) is the number of tiles out of place (not counting the blank). 2. A* search using the Manhattan heuristic function. 3. Iterative deepening A* with the Manhattan heuristic function. 4. Depth-first Branch and Bound with the Manhattan heuristic function. When defining the successor function, it is helpful to define the actions in terms of the empty tile, that is, the four actions are moving the empty tile right, down, left, and up. Consider the actions in this order in your implementation. If your algorithms take too long or too much memory to find any solution, your implementation may be inefficient. Consider optimizing it. If you still can't find solutions within a reasonable amount of time, enforce a time limit, say 30 minutes, on your algorithm and specify it in your report. Problem Analysis: For all the algorithms, include in your report a table the number of nodes expanded, the total time required to solve the puzzle, and the sequence of moves in the optimal solution. For Depth-first Branch and Bound, also record the time the optimal solution is found (typically not the same as the finish time). Deliverables: 1) Well commented code (JAVA). 2) A readme file explaining how to compile and run your code. 3) A written report explaining your experimental results and analysis.
Transcribed Image Text:Artificial Intelligence programming assignment Here is the goal state and four start states for the 8-puzzle. Goal: Easy: Medium: Hard: Worst: 1 2 3 5 6 7 1 3 4 8 6 2 2 8 1 2 8 1 8 4 4 3 4 6 3 4 8. 76 5 7 7 6 5 7 5 3 2 1 Implement the following search algorithms and test them on the start states and goal state shown above. Only A* needs to detect duplicate states and eliminate them from the remainder of the search. 1. A* search using the heuristic function f*(n) = g(n) + h*(n), where h*(n) is the number of tiles out of place (not counting the blank). 2. A* search using the Manhattan heuristic function. 3. Iterative deepening A* with the Manhattan heuristic function. 4. Depth-first Branch and Bound with the Manhattan heuristic function. When defining the successor function, it is helpful to define the actions in terms of the empty tile, that is, the four actions are moving the empty tile right, down, left, and up. Consider the actions in this order in your implementation. If your algorithms take too long or too much memory to find any solution, your implementation may be inefficient. Consider optimizing it. If you still can't find solutions within a reasonable amount of time, enforce a time limit, say 30 minutes, on your algorithm and specify it in your report. Problem Analysis: For all the algorithms, include in your report a table the number of nodes expanded, the total time required to solve the puzzle, and the sequence of moves in the optimal solution. For Depth-first Branch and Bound, also record the time the optimal solution is found (typically not the same as the finish time). Deliverables: 1) Well commented code (JAVA). 2) A readme file explaining how to compile and run your code. 3) A written report explaining your experimental results and analysis.
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