Answers.Body: <p>I would recommend looking at <a href="https://www.nature.com/articles/nature14236" rel="nofollow noreferrer">Deep Q-Learning</a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-07-02T14:46:22.187Z
Answers.Text: Is DQN really good when there are infinite different states the environment can be
Answers.UserDisplayName: SirPVP
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-07-02T15:16:58.717Z
Answers.Text: @SirPVP Yes, it is a function approximator method which is precisely for infinite state spaces.
Answers.UserDisplayName: David
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-07-02T10:17:17.193Z
Answers.LastActivityDate: 2020-07-02T10:17:17.193Z
Answers.UserDisplayName: David
Body: <p>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?</p>
  
Tags: <reinforcement-learning><algorithm><dqn><ddpg>
Title: What reinforcement learning algorithm should I use in continuous states?
UserDisplayName: SirPVP
ThreadText: # What reinforcement learning algorithm should I use in continuous states?
  
  (Asked by: username_0 on 2020-07-02)
  
  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?
  
  **Tags:** reinforcement-learning, algorithm, dqn, ddpg
  
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  ## 1 answers
  
  ### Answer by username_1 on 2020-07-02. Score: 0 | Accepted answer
  
  I would recommend looking at [Deep Q-Learning](https://www.nature.com/articles/nature14236).
  
  > **Comments:**
  > **username_0**: Is DQN really good when there are infinite different states the environment can be  
  > **username_1**: @SirPVP Yes, it is a function approximator method which is precisely for infinite state spaces.  
  
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