Body: <p>I understand some recent chess engines (like alphazero or muzero) are based on neural networks.  This question is not specific to chess, any other game (e.g. go) would do, but I keep chess for concreteness.</p>
  <p>I am not interested how these engines are trained but how they &quot;look like&quot; <em>after</em> training.  (For concreteness, it suffices for me that they give a &quot;score&quot; for a given board position.)  Somewhat similar questions have been asked <a href="https://ai.stackexchange.com/questions/34876/how-do-neural-networks-play-chess">here</a> but I can't find what I need.</p>
  <ol start="0">
  <li><p>Is it correct to view them as a neural network?  Or, is there some other major component like search trees or other type of algorithm.  I'm assuming that answer here is &quot;yes&quot; in an approriate sense.  Note: The <a href="https://arxiv.org/abs/1712.01815" rel="nofollow noreferrer">alpha zero paper</a> talks about various forms of tree search.  It is not clear to me how they are used to play, and from the appendix apparently some other engines use very limited search, like depth 2?  That would be already interesting to me.</p>
  </li>
  <li><p>What is the depth of the network?  Any reference to precise parameters?</p>
  </li>
  <li><p>What is the input and output format of these networks?  Is the input just an array with pieces positions (excluding three-fold repetition rules and similar secondary issues).  What is the output?
  Some info is <a href="https://ai.stackexchange.com/questions/26412/clarifying-representation-of-neural-nerwork-input-for-chess-alpha-zero">here</a> but I can't quite understand how it works specifically e.g. for chess.</p>
  </li>
  <li><p>What activation functions are used?</p>
  </li>
  </ol>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-05-17T20:15:18.723Z
Comments.Text: This is far too broad.
Comments.UserDisplayName: Chenmunka
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-05-18T13:47:34.043Z
Comments.Text: Please, vote to close it as "needs more focus" @Chenmunka
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-05-18T13:48:19.693Z
Comments.Text: Hello Manu. You're indeed asking too many questions in the same post. It's perfectly fine to have multiple questions and you questions seem interesting, but you should split this post into multiple ones, one for each question, unless they are really very related. As a rule of thumb, if you can't write your title as a specific question, then it means you need to split your post.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-05-19T14:00:49.667Z
Comments.Text: OK.  I put another question here https://ai.stackexchange.com/questions/45750/how-do-neural-network-chess-engines-select-moves
Comments.UserDisplayName: Manu
Tags: <neural-networks><chess>
Title: Structure and parameters of modern AI-baed chess engines
UserDisplayName: Manu
ThreadText: # Structure and parameters of modern AI-baed chess engines
  
  (Asked by: username_0 on 2024-05-17)
  
  I understand some recent chess engines (like alphazero or muzero) are based on neural networks. This question is not specific to chess, any other game (e.g. go) would do, but I keep chess for concreteness.
  
  I am not interested how these engines are trained but how they "look like" *after* training. (For concreteness, it suffices for me that they give a "score" for a given board position.) Somewhat similar questions have been asked [here](https://ai.stackexchange.com/questions/34876/how-do-neural-networks-play-chess) but I can't find what I need.
  
  0. Is it correct to view them as a neural network? Or, is there some other major component like search trees or other type of algorithm. I'm assuming that answer here is "yes" in an approriate sense. Note: The [alpha zero paper](https://arxiv.org/abs/1712.01815) talks about various forms of tree search. It is not clear to me how they are used to play, and from the appendix apparently some other engines use very limited search, like depth 2? That would be already interesting to me.
  1. What is the depth of the network? Any reference to precise parameters?
  2. What is the input and output format of these networks? Is the input just an array with pieces positions (excluding three-fold repetition rules and similar secondary issues). What is the output?
     Some info is [here](https://ai.stackexchange.com/questions/26412/clarifying-representation-of-neural-nerwork-input-for-chess-alpha-zero) but I can't quite understand how it works specifically e.g. for chess.
  3. What activation functions are used?
  
  **Tags:** neural-networks, chess
  > **Comments:**
  > **username_1**: This is far too broad.  
  > **username_2**: Please, vote to close it as "needs more focus" @Chenmunka  
  > **username_2**: Hello Manu. You're indeed asking too many questions in the same post. It's perfectly fine to have multiple questions and you questions seem interesting, but you should split this post into multiple ones, one for each question, unless they are really very related. As a rule of thumb, if you can't write your title as a specific question, then it means you need to split your post.  
  > **username_0**: OK.  I put another question here https://ai.stackexchange.com/questions/45750/how-do-neural-network-chess-engines-select-moves  
  
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  ## 0 answers
  
  