0
$\begingroup$

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?

$\endgroup$
0
$\begingroup$

I would recommend looking at Deep Q-Learning.

| improve this answer | |
$\endgroup$
  • $\begingroup$ Is DQN really good when there are infinite different states the environment can be $\endgroup$ – SirPVP Jul 2 at 14:46
  • $\begingroup$ @SirPVP Yes, it is a function approximator method which is precisely for infinite state spaces. $\endgroup$ – David Ireland Jul 2 at 15:16
  • 1
    $\begingroup$ Thank you very much. $\endgroup$ – SirPVP Jul 2 at 17:14

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.