Discussion of article "Random Decision Forest in Reinforcement learning" - page 7

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FxTrader562:

Can you please provide me one example code of an indicator without fuzzy logic and where to put the indicator in the current implementation of the code?

Now I can't, I'll try tonight.

 
mov :

Now I can not, I'll try in the evening.

OK, thank you. I will wait.

Basically, I just want to know how to feed other indicators like MACD,SAR, MA etc to the policy matrix to update policy and update reward on every profit and loss. It should be without fuzzy logic.

 

FxTrader562:

Basically, I just want to know how to feed other indicators like MACD,SAR, MA etc to the policy matrix to update policy and update reward on every profit and loss. It should be without fuzzy logic.

I looked at my code, it is a horrible mishmash of different algorithms being checked. For the sake of simplicity, I have added the necessary points for working without fuzzy logic into the source code of the article. I hope the author will not be offended. I checked it, it seems to work and I haven't forgotten anything important. The number of indicators is set by nIndicat.

 
mov :

I looked at my code, a terrible mess of different verifiable algorithms. For simplicity, I introduced the necessary elements for the work without fuzzy to the source code of the article. I hope the author will not be offended. I checked, it seemed to work. The number of indicators specifies nIndicat.

Thank you for the code. I will look into it.

By the way, one more thing. If you have tried to automate the optimisation process for iterative learning, then kindly let me know. I mean if you have any solution to run the optimiser automatically so that the EA will automatically call the optimiser upon every loss, then please let me know.

The author has told me that he will add the auto-optimisation feature in the future articles. But if someone else already has the code, then it will be great. Since the EA automatically maintains the optimal policy in the text files and hence, it is only required to run the optimiser automatically at regular intervals which I think is easy to implement.But I don't know how to do it.

 
FxTrader562: If you have tried to automate the optimisation process for iterative learning, then kindly let me know.

I tried, but my efficiency is much lower. As you would expect a new article by the author.

 
mov:

I tried, but my efficiency is much lower. As you would expect a new article by the author.

Anyway, thank you. I am also trying as well as waiting for the update from the author.

The code which you provided seems to work fine. I will try with various combinations and may update you again.

Many thanks again.

 
Hello people ,
First of all I would like to congratulate Maxim Dmitrievsky for his article.
Secondly, I want to say that I am keeping an eye on the topic, because the subject is very interesting.
Thirdly I would like to take a doubt because I am not able to understand how the execution of the reward in the EA of classification is made today, could anyone describe it?

What I understood is that when the EA closes the position with a negative value it makes a change in the 2 indexes of the vector (3 and 4).
Is anyone eligible? How do I know this reward is good? because I would like to increase the rewards when the operation is positive and take a certain amount of points.
//+------------------------------------------------------------------+
//||
//+------------------------------------------------------------------+
void updateReward()
  {
   if(MQLInfoInteger(MQL_OPTIMIZATION)==true)
     {
      int unierr;
      if(getLAstProfit()<0)
        {
         double likelyhood=MathRandomUniform(0,1,unierr);
         RDFpolicyMatrix[numberOfsamples-1].Set(3,likelyhood); // HERE 
         RDFpolicyMatrix[numberOfsamples-1].Set(4,1-likelyhood); // AND HERE 
        }
     }
  }


Thank you.
Ps. I used Google Translate, sorry if it is not understandable.
 
rogivilela:
What I understood is that when the EA closes the position with a negative value it makes a change in the 2 indexes of the vector (3 and 4).
Is anyone eligible? How do I know this reward is good? because I would like to increase the rewards when the operation is positive and take a certain amount of points.

You take the text from the article, look at the posts above, there is a constant discussion about the best reward, there are suggestions for more effective rewards.

 
rogivilela:

How do I know this reward is good?

If there is a loss, the algorithm should try not to trade or trade in the opposite direction, we do not know how to do it correctly, we use a random value. There is no other meaning in these lines

 
mov:

If a loss, the algorithm should try not to trade or trade in the opposite direction, we don't know the right way, we use a random value. There is no other meaning in the above lines

the article itself and the given algorithm has an introductory character, to get the result and not only in the tester you need to prepare the input data, I have recently been watching a lot of videos on YouTube on this topic, here is a very informative example, and the channel as a whole.


to start with I think to train by hours, i.e. 24 trained neural networks, because at different times of the day different volatility, and then we'll see.
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