Answers.Body: <p>Stockfish is free software (<a href="https://github.com/official-stockfish/Stockfish" rel="nofollow noreferrer">source</a> while AlphaGo can only be used by employees at Deepmind. This is important, because it means all answers to this question can only rely on the AlphaGo paper. Some decisions during the matches (e.g. giving limited time per move and not per game; giving different computational power) lead to unclarity how good alpha go really is.</p>
  
  <p><a href="https://en.m.wikipedia.org/wiki/Stockfish_(chess)" rel="nofollow noreferrer">Stockfish</a>  uses Alpha-beta search with a hardcoded metric to evaluate how good a position is.</p>
  
  <p>In contrast, AlphaGo uses Monte Carlo tree search and convolutional neural networks. They are trained in an reinforcement learning setting.</p>
  
  <p>AlphaGo is promoted as being almost directly applicable to different settings (Go, Chess), while stockfish is only applied to Chess. The techniques of stockfish can also be applied to Go, but the problem is the board evaluation. For Chess it's easy compared to Go.</p>
  
  <h2>References</h2>
  
  <ul>
  <li><a href="https://arxiv.org/abs/1712.01815" rel="nofollow noreferrer">Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm</a>, December 2017.</li>
  <li><a href="https://deepmind.com/documents/119/agz_unformatted_nature.pdf" rel="nofollow noreferrer">Mastering the Game of Go without Human Knowledge</a> is about Alpha Go Zero</li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-11-22T08:02:22.980Z
Answers.Text: Your references to AlphaGo should be to AlphaZero, although AlphaZero is derived from work on AlphaGo, and AlphaGo Zero.
Answers.UserDisplayName: Neil Slater
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-11-22T06:51:37.413Z
Answers.LastActivityDate: 2018-11-22T09:41:18.810Z
Answers.LastEditDate: 2018-11-22T09:41:18.810Z
Answers.UserDisplayName: Martin Thoma
Body: <p>I don't know much about AI or chess engines, but what is the fundamental difference between AlphaZero and Stockfish or Rybka?</p>
  
Tags: <chess>
Title: How is AlphaZero different from Stockfish or Rybka?
UserDisplayName: Siddhartha
ThreadText: # How is AlphaZero different from Stockfish or Rybka?
  
  (Asked by: username_0 on 2018-11-22)
  
  I don't know much about AI or chess engines, but what is the fundamental difference between AlphaZero and Stockfish or Rybka?
  
  **Tags:** chess
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2018-11-22. Score: 3
  
  Stockfish is free software ([source](https://github.com/official-stockfish/Stockfish) while AlphaGo can only be used by employees at Deepmind. This is important, because it means all answers to this question can only rely on the AlphaGo paper. Some decisions during the matches (e.g. giving limited time per move and not per game; giving different computational power) lead to unclarity how good alpha go really is.
  
  [Stockfish](https://en.m.wikipedia.org/wiki/Stockfish_(chess)) uses Alpha-beta search with a hardcoded metric to evaluate how good a position is.
  
  In contrast, AlphaGo uses Monte Carlo tree search and convolutional neural networks. They are trained in an reinforcement learning setting.
  
  AlphaGo is promoted as being almost directly applicable to different settings (Go, Chess), while stockfish is only applied to Chess. The techniques of stockfish can also be applied to Go, but the problem is the board evaluation. For Chess it's easy compared to Go.
  
  ## References
  
  * [Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm](https://arxiv.org/abs/1712.01815), December 2017.
  * [Mastering the Game of Go without Human Knowledge](https://deepmind.com/documents/119/agz_unformatted_nature.pdf) is about Alpha Go Zero
  
  > **Comments:**
  > **username_2**: Your references to AlphaGo should be to AlphaZero, although AlphaZero is derived from work on AlphaGo, and AlphaGo Zero.  
  
  ---
  
  