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mplementation Part Use appropriate data structure for the given search space and heuristic values.  Finding the child nodes (neighbors). Using correct formula to compute the path cost.  Appropriately usage of frontier set (open/priority queue) and explore set (closed/ visited).  Show the results.

mplementation Part Use appropriate data structure for the given search space and heuristic values.  Finding the child nodes (neighbors). Using correct formula to compute the path cost.  Appropriately usage of frontier set (open/priority queue) and explore set (closed/ visited).  Show the results.

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Implementation Part
Use appropriate data structure for the given search space and heuristic values. 
Finding the child nodes (neighbors).
Using correct formula to compute the path cost. 
Appropriately usage of frontier set (open/priority queue) and explore set (closed/ visited). 
Show the results.

City Heuristic Muscat 200 Sur 150 Seeb 131 Nizwa 125 Bawshar 165 Ibri 78 Duqm 157 Jabrin 300 Bahla 421 Buraimi 321 Manah 412 Ruwi 477 Sohar 342 Salalah Describe step-by-step procedure to find the route from Muscat to Salalah using the A* algorithm. Justify the optimality of obtained path based on admissibility and consistency. > Write a Python program to find the path from Muscat to Salalah using the above- mentioned search space and the heuristic table.
Transcribed Image Text:City Heuristic Muscat 200 Sur 150 Seeb 131 Nizwa 125 Bawshar 165 Ibri 78 Duqm 157 Jabrin 300 Bahla 421 Buraimi 321 Manah 412 Ruwi 477 Sohar 342 Salalah Describe step-by-step procedure to find the route from Muscat to Salalah using the A* algorithm. Justify the optimality of obtained path based on admissibility and consistency. > Write a Python program to find the path from Muscat to Salalah using the above- mentioned search space and the heuristic table.
Problem: Finding shortest route among different cities On a road map, a road connecting two cities is typically labeled with its distance. We can model a road network as a graph whose edges are labeled with real numbers. These numbers represent the distance (or other cost metric, such as travel time) between two vertices (cities). These labels may be called weights, costs, or distances, depending on the application. Given such a graph of Muscat city, a problem is to find the shortest route and the total cost of this route for any two given cities of Muscat. The graph is given as below Sur 112 212 Muscat 63 15 Bawshar Seeb 56 121 130 Nizwa 300 Sohar 121 Ibri 221 119 Salalah 99 Buraimi 160 291 117 219 Duqm Ruwi 165 88 98 121 Manah Bahla 210 Jabrin A* Algorithm For the given start-state and goal-state Muscat and Salalah, respectively, the heuristic values are given as below
Transcribed Image Text:Problem: Finding shortest route among different cities On a road map, a road connecting two cities is typically labeled with its distance. We can model a road network as a graph whose edges are labeled with real numbers. These numbers represent the distance (or other cost metric, such as travel time) between two vertices (cities). These labels may be called weights, costs, or distances, depending on the application. Given such a graph of Muscat city, a problem is to find the shortest route and the total cost of this route for any two given cities of Muscat. The graph is given as below Sur 112 212 Muscat 63 15 Bawshar Seeb 56 121 130 Nizwa 300 Sohar 121 Ibri 221 119 Salalah 99 Buraimi 160 291 117 219 Duqm Ruwi 165 88 98 121 Manah Bahla 210 Jabrin A* Algorithm For the given start-state and goal-state Muscat and Salalah, respectively, the heuristic values are given as below
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