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I want to use reinforcement learning in an environment I made. The exact environment doesn't really matter, but it comes down to this: The amount of different states in the environment is infinite e.g. amount of ways you can put 4 cars at an intersection, but the amount of different actions is only 3 e.g. go forward, right or left. The state exists out of five numbers. My question is: what algorithm should I use or at least what kind of algorithm?

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I would recommend looking at Deep Q-Learning.

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  • $\begingroup$ Is DQN really good when there are infinite different states the environment can be $\endgroup$
    – SirPVP
    Jul 2, 2020 at 14:46
  • $\begingroup$ @SirPVP Yes, it is a function approximator method which is precisely for infinite state spaces. $\endgroup$ Jul 2, 2020 at 15:16
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    $\begingroup$ Thank you very much. $\endgroup$
    – SirPVP
    Jul 2, 2020 at 17:14

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