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In RL, in a game situation, usually the agent is trained by playing against itself.

When we should not depend on this self-training, and switch to train the agent with a real or different player agent other than the agent it self?

I mean is there any characteristics of the environment that would make self-play worse choice than playing against an existing player?

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Ideally when training an agent you would reach an equilibrium between both player strategies strategies (hopefully a Nash equilibrium). When using only self-play this equilibrium might be different to the one you would reach when competing against a specific player, in particular, taking into consideration that the other player might not be very efficient, may have a different reward structure, etc.

Now, answering your specific question about the environment.. I would say that the critical aspect is the game being played. You should check if you are dealing with a zero-sum game, cooperative vs non-cooperative, etc.

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  • $\begingroup$ Thanks for the answer. Can you elaborate on the last paragraph? You say to check whether it's zero-sum or not, cooperative or not, etc. Then what should we do with that information, once we have it? How do the answers to those questions affect whether self-play will be more or less effective? Thank you! $\endgroup$ – D.W. Nov 11 '16 at 15:45

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