Mix action channels are not supported in DDPG
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Sania Gul
il 18 Set 2024 alle 6:07
Commentato: Sania Gul
il 18 Set 2024 alle 9:04
My action space is mixed. Except one, all variables are continuous. So, I have defined the action apace as shown in the code below for a DDPG agent. But I get the error as shown in the attached image.
actInfoCont = rlNumericSpec([255 1],"UpperLimit",1,"LowerLimit",0); % (0 to 1 probabilistic mask)
actInfoDIsc = rlFiniteSetSpec([0 3.141592654]);
actInfo = [actInfoCont actInfoDIsc];
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Ayush Aniket
il 18 Set 2024 alle 6:32
Modificato: Ayush Aniket
il 18 Set 2024 alle 6:32
Hi Sania,
Currently, Reinforcement Learning Toolbox does not support mixed action spaces. As an alternative you could consider training two agents, one for the continuous action and another for the discrete. Refer to the following MATLAB Answer: https://www.mathworks.com/matlabcentral/answers/2015776-reinforcement-learning-agent-for-mixed-action-space
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