Body: <p>In some learning algorithms, we don't directly train models by datasets with labels to predict, but rather we create 2 competing models and let them fight/compete against each other.  As the many millions of epochs pass, the models fight each other, and every time each model improves itself (further optimise its weights) to win.  After many epochs of the models smashing each other, eventually they become really strong super-hero models that can totally blow any human out of the water.  This approach seems to be often used with machine learning models that are tasked to play multiplayer games.  Instead of letting them play with the slow humans, they fight with each other to death for many many epochs to become way stronger than any human can naturally be.</p>
  <p>What is the name of such kind of machine learning approach?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-05T09:42:16.930Z
Comments.Text: You can actually cut down a lot of your question. Are you talking about actor-critic approaches? There are also GANs (Generative Adversarial Networks)
Comments.UserDisplayName: N. Kiefer
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-05T09:44:24.650Z
Comments.Text: True, and yes.  Post an answer and get some internet points now!
Comments.UserDisplayName: caveman
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-05T09:47:22.727Z
Comments.Text: @N.Kiefer - BTW [someone here](https://towardsdatascience.com/multi-agent-reinforcement-learning-and-the-future-of-ai-524fc1b5e25) seems to be calling it "multi-agent reinforcement learning".  What do you think?  Is it not the same thing?
Comments.UserDisplayName: caveman
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-05T09:49:43.300Z
Comments.Text: I haven't heard of that before, while it seems to fit your question better, I feel like my mentioned methods are more widespread.
Comments.UserDisplayName: N. Kiefer
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-05T10:17:10.563Z
Comments.Text: Here’s a [link](https://openai.com/blog/competitive-self-play/) about what they call “competitive self-play.” Also, another [link](https://openai.com/blog/emergent-tool-use/) from the same source mentioning multi-agent reinforcement learning.
Comments.UserDisplayName: S2673
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-05T14:50:27.483Z
Comments.Text: actor-critic or adversarial models.
Comments.UserDisplayName: David Hoelzer
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Comments.CreationDate: 2021-05-06T10:56:14.207Z
Comments.Text: I wouldn’t say there is competition in actor-critic models. The critic is guessing returns to help actor updates, not trying to become better than the actor.
Comments.UserDisplayName: S2673
Tags: <machine-learning><deep-learning>
Title: What is the name of algorithms that train by competing each other?
UserDisplayName: caveman
ThreadText: # What is the name of algorithms that train by competing each other?
  
  (Asked by: username_0 on 2021-05-05)
  
  In some learning algorithms, we don't directly train models by datasets with labels to predict, but rather we create 2 competing models and let them fight/compete against each other. As the many millions of epochs pass, the models fight each other, and every time each model improves itself (further optimise its weights) to win. After many epochs of the models smashing each other, eventually they become really strong super-hero models that can totally blow any human out of the water. This approach seems to be often used with machine learning models that are tasked to play multiplayer games. Instead of letting them play with the slow humans, they fight with each other to death for many many epochs to become way stronger than any human can naturally be.
  
  What is the name of such kind of machine learning approach?
  
  **Tags:** machine-learning, deep-learning
  > **Comments:**
  > **username_1**: You can actually cut down a lot of your question. Are you talking about actor-critic approaches? There are also GANs (Generative Adversarial Networks)  
  > **username_0**: True, and yes.  Post an answer and get some internet points now!  
  > **username_0**: @N.Kiefer - BTW [someone here](https://towardsdatascience.com/multi-agent-reinforcement-learning-and-the-future-of-ai-524fc1b5e25) seems to be calling it "multi-agent reinforcement learning".  What do you think?  Is it not the same thing?  
  > **username_1**: I haven't heard of that before, while it seems to fit your question better, I feel like my mentioned methods are more widespread.  
  > **username_2**: Here’s a [link](https://openai.com/blog/competitive-self-play/) about what they call “competitive self-play.” Also, another [link](https://openai.com/blog/emergent-tool-use/) from the same source mentioning multi-agent reinforcement learning.  
  > **username_3**: actor-critic or adversarial models.  
  > **username_2**: I wouldn’t say there is competition in actor-critic models. The critic is guessing returns to help actor updates, not trying to become better than the actor.  
  
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  ## 0 answers
  
  