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Update greedy-best-first-search.md #3568
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Improving Greedy Best First Search algorithm.
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@Sahilkumar19 I did a first review and had one suggestion revising your edits for clarity. You also need to sigh the CLA.
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| **Greedy best-first search** is an informed search algorithm where the evaluation function is strictly equal to the heuristic function, disregarding the edge weights in a weighted graph. To get from a start node to a target node, the lowest value resulting from some heuristic function, **h(x)**, is considered as the successive node to traverse to. The goal is to choose the quickest and shortest path to the target node. | ||
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| **Greedy best-first search** is an informed search algorithm where the evaluation function is strictly equal to the heuristic function, disregarding the edge weights in a weighted graph(because we care about the heuristic value). In ordre to search for a goal node expand the node that is closest to the goal as determined by the heuristic function.Assume that is likely to lead a solution quickly.The solution from Greedy Best First Search may not be optimal since a shorter path may exist.In this algorithm search cost is minimum since solution found without expanding a node that is not on the solution path.This algorithm is minimal but not complete since it can lead to a dead end.It's called "Greedy" since at each step it tries to get as close to the goal as it can. |
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| **Greedy best-first search** is an informed search algorithm where the evaluation function is strictly equal to the heuristic function, disregarding the edge weights in a weighted graph(because we care about the heuristic value). In ordre to search for a goal node expand the node that is closest to the goal as determined by the heuristic function.Assume that is likely to lead a solution quickly.The solution from Greedy Best First Search may not be optimal since a shorter path may exist.In this algorithm search cost is minimum since solution found without expanding a node that is not on the solution path.This algorithm is minimal but not complete since it can lead to a dead end.It's called "Greedy" since at each step it tries to get as close to the goal as it can. | |
| **Greedy best-first search** is an informed search algorithm where the evaluation function is strictly equal to the heuristic function, disregarding the edge weights in a weighted graph because it only cares about the heuristic value. In order to search for a goal node it expands the node that is closest to the goal as determined by the heuristic function. This assumes that it is likely to lead to a solution quickly. However, the solution from Greedy best-first search may not be optimal since a shorter path may exist. | |
| In this algorithm the search cost is at a minimum since the solution is found without expanding a node that is not on the solution path. This algorithm is minimal, but not complete, since it can lead to a dead end. It's called "Greedy" because at each step it tries to get as close to the goal as it can. |
Thanks for reviewing and suggestions. |
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@Sahilkumar19 I made one typo edit and looks good for a second review.
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@Sahilkumar19 I did my review. The second review will be by one of the other maintainers. |
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@Sahilkumar19 @SSwiniarski I just made some direct edits to clean up a couple of typos and adjust the phrasing a bit. LGTM
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👋 @Sahilkumar19 🎉 Your contribution(s) can be seen here: https://www.codecademy.com/resources/docs/ai/search-algorithms/greedy-best-first-search Please note it may take a little while for changes to become visible. |
Fixes #3565
This PR improving the content of Greedy Best First algorithm.I have added point which were missing or unclear in the provided explanation.