How can I have several actions for a DQN in the Reinforcement Learning Toolbox?
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I'm trying to define the output of a DQN agent with a custom environment, and can't use the actionInfo = rlFiniteSetSpec() correctly.
I'm trying to control 3 actuators that will receive commands 0 and 1.
I always get number of actions = 1.
And the documentation is not clear as it's a new toolbox.
Any suggestions?
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Huzaifah Shamim
2020년 7월 9일
Oh nice okok. What custom environment where you trying to make?
Also how should I approach it if i have 3 agents (like your three actuators) but 12 actions could be applied to them?
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Emmanouil Tzorakoleftherakis
2019년 5월 11일
If you type
help rlFiniteSetSpec
the second example is
spec = rlFiniteSetSpec({[0,1];[1,1];[1,2];[1,3]})
If you define all possible combinations of the discrete inputs in a cell array as above, that should work (think of a single action as one possible combination of your 3 actuator commands).
I hope this helps.
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