Answers.Body: <p>One example might be self-play in games. Since neural networks and deep learning depend on massive amounts of data, one way to generate data is to have two virtual machines play each other and record the experience. An example discussion can be found at <a href="http://www.cs.cornell.edu/boom/2001sp/Tsinteris/gammon.htm">http://www.cs.cornell.edu/boom/2001sp/Tsinteris/gammon.htm</a> which uses reinforcement learning. I believe <a href="https://deepmind.com/research/alphago/">AlphaGo</a> also uses this technique of self-play, and uses two independent neural networks, one reducing the search space and the other deciding on the best move in the remaining space, that in a sense cooperate to decide on the next move.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-01-28T08:06:51.220Z
Answers.LastActivityDate: 2017-01-28T08:06:51.220Z
Answers.UserDisplayName: Colin Beckingham
Body: <p>I am talking about relationships between AIs (e.g. 2 of them forming a couple, 3+ in family like relationship).</p>
  
  <p>What knowledge could come out of such experimentation?</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-11-02T18:58:45.887Z
Comments.Text: Does [swarm robotics](https://en.wikipedia.org/wiki/Swarm_robotics) fit your question?
Comments.UserDisplayName: Basile Starynkevitch
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-11-02T19:27:46.650Z
Comments.Text: If there is a single/common goal, how do define the boundaries between the AIs if they are integrated in one system? If there are separate goals for each of the AIs then what is the interaction for?
Comments.UserDisplayName: Iliyan Bobev
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-11-03T09:04:57.677Z
Comments.Text: https://en.wikipedia.org/wiki/Generative_adversarial_networks
Comments.UserDisplayName: BlindKungFuMaster
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-11-03T14:38:04.940Z
Comments.Text: @Basile Starynkevitch: Yes definitely! I would like to get an input on that as well. I actually did not think of it at first.
Comments.UserDisplayName: K_Rol
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-11-04T11:19:46.717Z
Comments.Text: For physical example, see: [How can thousand-robot swarm coordinate their moves without bumping into each other?](http://ai.stackexchange.com/q/1426/8)
Comments.UserDisplayName: kenorb
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2016-11-04T11:23:11.647Z
Comments.Text: Similar: [Which deep networks are scalable in terms of “talking” to each other?](http://ai.stackexchange.com/q/160/8)
Comments.UserDisplayName: kenorb
Tags: <emotional-intelligence><human-like>
Title: Were there known tests done on two or more AI interacting together?
UserDisplayName: K_Rol
ThreadText: # Were there known tests done on two or more AI interacting together?
  
  (Asked by: username_0 on 2016-11-01)
  
  I am talking about relationships between AIs (e.g. 2 of them forming a couple, 3+ in family like relationship).
  
  What knowledge could come out of such experimentation?
  
  **Tags:** emotional-intelligence, human-like
  
  > **Comments:**
  > **username_1**: Does [swarm robotics](https://en.wikipedia.org/wiki/Swarm_robotics) fit your question?  
  > **username_2**: If there is a single/common goal, how do define the boundaries between the AIs if they are integrated in one system? If there are separate goals for each of the AIs then what is the interaction for?  
  > **username_3**: https://en.wikipedia.org/wiki/Generative_adversarial_networks  
  > **username_0**: @username_1: Yes definitely! I would like to get an input on that as well. I actually did not think of it at first.  
  > **username_4**: For physical example, see: [How can thousand-robot swarm coordinate their moves without bumping into each other?](http://ai.stackexchange.com/q/1426/8)  
  > **username_4**: Similar: [Which deep networks are scalable in terms of “talking” to each other?](http://ai.stackexchange.com/q/160/8)  
  
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  ## 1 answers
  
  ### Answer by username_5 on 2017-01-28. Score: 4
  
  One example might be self-play in games. Since neural networks and deep learning depend on massive amounts of data, one way to generate data is to have two virtual machines play each other and record the experience. An example discussion can be found at <http://www.cs.cornell.edu/boom/2001sp/Tsinteris/gammon.htm> which uses reinforcement learning. I believe [AlphaGo](https://deepmind.com/research/alphago/) also uses this technique of self-play, and uses two independent neural networks, one reducing the search space and the other deciding on the best move in the remaining space, that in a sense cooperate to decide on the next move.
  
  
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