Hello and welcome to this new tutorial.
So we've just got the puzzle rewards obtained by playing the perturbations in positive directions.
And I went to get the negative rewards.
That is the words obtained by playing the perturbations in the opposite directions as the previous ones.
This once and so it's going to be so easy now because we've done this and we're going to get these rewards
with the same values of the perturbations that is the Delta scale here for each of the six indirections.
But the only thing that will change your mind is where it is is of course the direction which this time
will be negative.
That is opposite to the previous ones so that we will be in this condition else which corresponds to
Elif directional co-equals negative.
And therefore it will return the matrix of weights minus which represent the opposite direction the
noise times the perturbation but it is the same value here of the perturbation Delta scale.
And so that when we explore the policy on the full episode for each of the six indirections the action
here will be played by evaluating the policy on the current state.
The same value of the perturbation Delta that it was simpled but the opposite direction here because
we are going to specify that the direction is negative.
So the only thing that we have to do is just take these two lines.
All right.
So I just copy them I'm getting here everything has to be well aligned.
I'm facing that then it's the exact same for loop.
But instead of specifying the other direction Well we're going to specified the negative direction.
And here you go.
This is done to get negative rewards.
And of course we need to replace you positive by negative to update our list of negative rewards variable
that contains all the rewards obtained by playing the perturbations in the opposite directions that
were applied here in the previous step.
All right so here we go we have our positive rewards now and our negative rewards.
And now what we're going to do is gather all of them.
All of these positive words and negative words in one same list.
So it will be a list of 32 words.
And why do we need to do this.
That's just to apply this 3.1 feature scaling by the standard deviation.
We want to scale the reward for Again performance purposes.
And so by scaling by standard deviation we will get Sigma R which is just one standard deviation of
the word and we'll integrate that factor here in the method definitive answers to our one step of Graylands
sent to update the policy.
So we'll do that in the next its oil.
It's going to be pretty easy.
We'll just gather all the words in one simplest and then using the SDD function will compute the standard
deviation of all the awards composing that list.
Let's do that in the next as oil.
And until then enjoy AAE.