using Q learning agent for continuous observation space
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Hello,
I have a reinforcement learning problem where the observation is the error of closed loop feedback and it is continuous, and discrete action space.
but Im a little bit confused about making critic using rlQValueRepresentation which its syntax mostly uses either a table or deep neural network,
and they are inappropriate for my work, as I didnt find any example like this in Mathworks website, Is there anyone who can help me on this?
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