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2_uninformed_search #12

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@SepehrAsh

8. Conclusion


## Introduction

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Please Fulfill The Introduction

It is not an optimal algorithm in general but if cost of steps be equal to one, this algorithm would be optimal.

As it is obvious this algorithm has some pros and cons. The benefit of it is that it is accurate and easy to run and implement. But if the goal be at depth 21, this algorithm would take hundreds of years to find the solution.

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You Can Add Some Examples Here

* Cutoff failure value: It defines no solution for the problem within a given depth limit.

Look at the example:
![](https://github.com/mohsenosl99/notes/blob/master/notebooks/2_uninformed_search/images/depth-limited-search-algorithm.png)

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You Can Describe The Example To Improve The Quality Of Your Lecture Note


**Space Complexity**

The space complexity of IDDFS will be O(bd).

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It Would Be Great To Explain More




## Conclusion

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Please Fulfill The Conclusion





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Please Add References, For Example : You Can Add Where You Read Articles About The Topic, or You can mention where students can find more information about the topic


The iterative search algorithm is useful uninformed search when search space is large, and depth of goal node is unknown.

**Example**

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Nice


> O(b^d(1 – 1/b)^-2)

Note: In this algorithm because of the fact that we want to avoid space problems, we won't store any data therefore we may have to repeat some actions but it won't trouble us because time complexity still remains O( b^d ), similar to BFS.

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Good Note





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  • You Can Add More Information


# Contents

1. Introduction

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Your Titles Should Be Clickable

2. Breadth-first Search
3. Uniform cost search
4. Depth-first Search
5. Depth-limited Search

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You would delete numbers.

@@ -0,0 +1,255 @@

# Uninformed Search

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Please explain what the term "Search" means exactly.

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You should explain in a way that everyone could read the article and understand the concept.

Iterative deepening depth-first search
Bidirectional search
Conclusion

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Please add tree search and graph search into your content.


**Completeness**

This algorithm is complete is ifthe branching factor is finite.

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Check your sentence.





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Full review:

  1. Please fulfill the Introduction. ( You can explain terms like "Search", "Optimality", etc in your introduction.
  2. You can add methods I've mentioned in your table of content.
  3. Please make your table of contents clickable.
  4. Discuss a little about your examples.

* Standard failure value: It indicates that problem does not have any solution.
* Cutoff failure value: It defines no solution for the problem within a given depth limit.

Look at the example:

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The position of the example's image could be better.

@mohsenosl99
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@SepehrAsh

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3 participants