1. A picture containing night sky Description automatically generated.
2. A picture containing factory, city, night Description automatically generated.
Black 3D wave patterns. 3. Application/Motivation.
Blue abstract showing data flow. Circles and an organic shape.
5. DAIICT Map:-. 00 RON. DA-IICT CAMPUS MAP FACULTY - • THEATRE-I LECTURE LECTURE CANTEEN COURT sac •1 SAC, Z BUSCALOVS.
Transforming the map into a graph, we have:-. 6. 10 13.
A city skyline at night Description automatically generated with medium confidence.
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A picture containing scene pier Description automatically generated.
10. A picture containing factory, city, night Description automatically generated.
Black 3D wave patterns. 11. We repeat the above steps until all nodes of the given graph are not visited. Finally, we get the following Path Graph. We see that the shortest distance between O and D is 14..
Blue abstract showing data flow. Circles and an organic shape.
A * search algorithm is one of the best graph search and method search algorithms, designed primarily for weighted graphs. Highly preferred because of its completeness and it’s overall efficiency. A better and efficient version of Dijkstra’s Algorithm..
This algorithm depends on 3 functions: g(n) represents cost of traversing from one node to another. h(n) represents heuristic approximation of the node's value. Which simply means approximation cost from the source node to the target node f(n) represents the final cost, i.e. f(n) = g(n) + h(n).
A city skyline at night Description automatically generated with medium confidence.
16. A picture containing text Description automatically generated.
A picture containing scene pier Description automatically generated.
Black 3D wave patterns. 18. Example : Let’s try to find the shortest route from college main gate(A) to canteen(H). First, We start off at initial point A, and push it in the open list. Then, let us move A to the closed list and check the possible nearby options and move them to open list..
Blue abstract showing data flow. Circles and an organic shape.
20. 3. We again choose the path with least F value, which is K. After K, the least F value option is H, the goal. Even though we reached the goal, we still don’t know if we are finished yet. 4. We move H to the open list and check the open list for the least F value, which is H. But, in this case H wasn’t the least F value option. We will continue the process till the goal is reached..
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