How to interpret the learnableParameters (Reinforcement Learning Toolbox)?

I was wondering how to interpret the tables that one is receiving when using this line:
params = getLearnableParameters (critic);
Why are there 6 tables after q learning for example? I expected one.

 Accepted Answer

The values in these tables refer to the weights for the critic network.

More Answers (1)

From my understanding you want to know why are there 6 values returned as the result of the getLearnableParameters function. I assume that you are running example in getLearnableParameters:
load('DoubleIntegDDPG.mat','agent')
critic = getCritic(agent);
params = getLearnableParameters(critic);
In this case since DoubleIntegDDPG.mat has 6 learnable parameters from the reinforcement learning policy (critic in your case) getLearnableParameters returns 6 values.

2 Comments

No. I figured it out: Those values in these 6 tables refer to the weights in my dnn. I appreciate your effort though.

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