Answers.Body: <p>Assuming that 'non-depth-limited minimax' is minimax with iterative deepening, it does not have to result in the same output as depth-limited minimax. It can traverse the tree deeper and thus find different optimal answers for a 'deeper' layer.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-05-03T16:18:59.403Z
Answers.LastActivityDate: 2022-05-03T16:18:59.403Z
Answers.UserDisplayName: Robin van Hoorn
Body: <p>I have read about a question that says the following:</p>
  <p>Why is depth-limited minimax preferable to minimax?</p>
  <p>One of the wrong answers was:</p>
  <blockquote>
  <p>The depth-limited minimax will achieve the same output as minimax without depth-limited, but can sometimes use less memory.</p>
  </blockquote>
  <p>Why is the above answer is wrong? I mean, don't both of these algorithms always achieve the same output, and because the depth-limited minimax doesn't always explore all the states this makes it use less memory?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-04-30T05:09:40.127Z
Comments.Text: Can you please provide a reference that describes this "depth-limited minimax"? I think you're not talking about alpha-beta pruning, but some other variation. Wikipedia provides the pseudocode for the depth-limited minimax [here](https://en.wikipedia.org/wiki/Minimax), but if you have a more reliable reference that you're using that describes it, feel free to share it with us. It might also be a good idea to provide the link to the original source of the question.
Comments.UserDisplayName: nbro
Tags: <search><minimax>
Title: Why is depth-limited is preferable to minimax without depth limited
UserDisplayName: Ahmed
ThreadText: # Why is depth-limited is preferable to minimax without depth limited
  
  (Asked by: username_0 on 2022-04-29)
  
  I have read about a question that says the following:
  
  Why is depth-limited minimax preferable to minimax?
  
  One of the wrong answers was:
  
  > The depth-limited minimax will achieve the same output as minimax without depth-limited, but can sometimes use less memory.
  
  Why is the above answer is wrong? I mean, don't both of these algorithms always achieve the same output, and because the depth-limited minimax doesn't always explore all the states this makes it use less memory?
  
  **Tags:** search, minimax
  
  > **Comments:**
  > **username_1**: Can you please provide a reference that describes this "depth-limited minimax"? I think you're not talking about alpha-beta pruning, but some other variation. Wikipedia provides the pseudocode for the depth-limited minimax [here](https://en.wikipedia.org/wiki/Minimax), but if you have a more reliable reference that you're using that describes it, feel free to share it with us. It might also be a good idea to provide the link to the original source of the question.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2022-05-03. Score: 1
  
  Assuming that 'non-depth-limited minimax' is minimax with iterative deepening, it does not have to result in the same output as depth-limited minimax. It can traverse the tree deeper and thus find different optimal answers for a 'deeper' layer.
  
  
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