YouTube Link: https://youtu.be/amlkE0g-YFU ** Artificial Intelligence and Deep Learning: https://www.edureka.co/ai-deep-learni... ** This Edureka PPT on 'A Star Algorithm' teaches you all about the A star Algorithm, the uses, advantages and disadvantages and much more. It also shows you how the algorithm can be implemented practically and has a comparison between the Dijkstra and itself. Check out our playlist for more videos: http://bit.ly/2taym8X Follow us to never miss an update in the future. YouTube: https://www.youtube.com/user/edurekaIN Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Castbox: https://castbox.fm/networks/505?country=in

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• What are Search Algorithms?
• Why A* Algorithm?
• In-and-Out of A* Algorithm
• A* Algorithm in Practicality

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5. What are Search Algorithms?
• Moving from one place to another is a task we do almost everyday
• Finding the shortest path by ourselves was difficult
• We now have algorithms that help us find that shortest route
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7. Why A* Algorithm?
Before the why, let’s understand what is A*
A* is an extended BFS Algorithm that prioritizes the shortest routes that it can reach first and then
the other routes. It is optimal and complete.
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8. OP
Why A* Algorithm?
A* is sure to give you the best
solution that is available for the
problem
Optimal
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9. OP
Why A* Algorithm?
A* is sure to give you the best
solution that is available for the
problem
Optimal Complete
A* is to find all the possible
solutions that exist for the problem
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10. OP
Why A* Algorithm?
Dijkstra does not know when to stop
as it does not know which is the best
path and tends to compute
inefficiently
A* computes the best possible way
and stops when the best route is
found. This makes the computations
effective and efficient
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12. In-and-Out of A*
Algorithm
• This formula is the heart and soul of
this algorithm
• These help in optimizing and finding
the efficient path
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13. In-and-Out of A* Algorithm
• This parameter is used to find the
least cost from one node to the other
F = G + H
• Responsible to find the optimal path
between source and destination
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14. In-and-Out of A* Algorithm
• This parameter is the cost of moving
from node to another
F = G + H
• The parameter changes for every
movement from one node to other
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15. In-and-Out of A* Algorithm
• This parameter is the heuristic path
between current node to destination
F = G + H
• Not actual cost but is the assumption
cost from the node to destination
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16. In-and-Out of A*
Algorithm
• Let’s understand how the calculation
works out
• Our graph here which has a source S,
Destination E and other nodes
S
BA
E
1 2
13 5
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17. In-and-Out of A*
Algorithm
The cost to enter the source is the travel
cost, zero and heuristic cost which is 5
S
BA
E
1 2
13 5
F = G + H
For source,
f = g + h = 0 + 5 = 5
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18. In-and-Out of A*
Algorithm
The travel cost through A is 5 and B is 7,
so we shall choose A for now
S
BA
E
1 2
13 5
For S-A, 1 + 4 = 5
For S-B, 2 + 5 = 7
Choose S-A
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19. In-and-Out of A*
Algorithm
The travel cost through SA to E is 14 and
SB to E is just 7. So we choose 7 as our
shortest path.
S
BA
E
1 2
13 5
For S-A-E, (1+13) + 0 = 14
For S-B-E, (2+5) + 0 = 7
Choose S-B-E
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20. In-and-Out of A* Algorithm
S
BA
E
1 2
13 5
The Final Path is S-B-E
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21. In-and-Out of A* Algorithm
Algorithm A*():
Add start node to list
For all the neighboring nodes, find the least cost F node
Switch to the closed list
For 8 nodes adjacent to the current node
If the node is not reachable, ignore it. Else
If the node is not on the open list, move it to the open list and calculate f, g, h.
If the node is on the open list, check if the path it offers is less than the current
path and change to it if it does so.
Stop working when
You find the destination
You cannot find the destination going through all possible points
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23. Let’s code!
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24. Copyright © 2017, edureka and/or its affiliates. All rights reserved.
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