| //+------------------------------------------------------------------+
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| //| Study.mq5 |
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| //| Copyright DNG® |
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| //| https://www.mql5.com/ru/users/dng |
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| //+------------------------------------------------------------------+
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| #property copyright "Copyright DNG®"
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| #property link "https://www.mql5.com/ru/users/dng"
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| #property version "1.00"
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| //+------------------------------------------------------------------+
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| //| |
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| //+------------------------------------------------------------------+
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| #define Study
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| #include "Trajectory.mqh"
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| //+------------------------------------------------------------------+
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| //| Input parameters |
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| //+------------------------------------------------------------------+
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| input int Iterations = 100000;
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| input float Tau = 0.01f;
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| //+------------------------------------------------------------------+
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| //| |
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| //+------------------------------------------------------------------+
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| STrajectory Buffer[];
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| CNet Actor;
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| CNet Critic1;
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| CNet Critic2;
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| CNet TargetCritic1;
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| CNet TargetCritic2;
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| //---
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| float dError;
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| datetime dtStudied;
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| //---
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| CBufferFloat State;
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| CBufferFloat Account;
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| CBufferFloat Actions;
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| CBufferFloat Gradient;
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| CBufferFloat *Result;
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| vector<float> SchedulerResult;
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| vector<float> check;
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| vector<float> ActorResult;
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| //---
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| COpenCLMy *OpenCL;
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| //+------------------------------------------------------------------+
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| //| Expert initialization function |
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| //+------------------------------------------------------------------+
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| int OnInit()
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| {
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| //---
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| ResetLastError();
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| if(!LoadTotalBase())
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| {
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| PrintFormat("Error of load study data: %d", GetLastError());
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| return INIT_FAILED;
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| }
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| //--- load models
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| float temp;
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| if(!Actor.Load(FileName + "Act.nnw", temp, temp, temp, dtStudied, true) ||
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| !Critic1.Load(FileName + "Crt1.nnw", temp, temp, temp, dtStudied, true) ||
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| !Critic2.Load(FileName + "Crt2.nnw", temp, temp, temp, dtStudied, true) ||
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| !TargetCritic1.Load(FileName + "Crt1.nnw", temp, temp, temp, dtStudied, true) ||
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| !TargetCritic2.Load(FileName + "Crt2.nnw", temp, temp, temp, dtStudied, true))
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| {
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| CArrayObj *actor = new CArrayObj();
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| CArrayObj *critic = new CArrayObj();
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| if(!CreateDescriptions(actor, critic))
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| {
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| delete actor;
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| delete critic;
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| return INIT_FAILED;
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| }
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| if(!Actor.Create(actor) || !Critic1.Create(critic) || !Critic2.Create(critic))
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| {
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| delete actor;
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| delete critic;
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| return INIT_FAILED;
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| }
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| if(!TargetCritic1.Create(critic) || !TargetCritic2.Create(critic))
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| {
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| delete actor;
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| delete critic;
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| return INIT_FAILED;
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| }
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| delete actor;
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| delete critic;
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| //---
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| TargetCritic1.WeightsUpdate(GetPointer(Critic1), 1.0f);
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| TargetCritic2.WeightsUpdate(GetPointer(Critic2), 1.0f);
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| }
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| //---
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| OpenCL = Actor.GetOpenCL();
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| Critic1.SetOpenCL(OpenCL);
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| Critic2.SetOpenCL(OpenCL);
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| TargetCritic1.SetOpenCL(OpenCL);
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| TargetCritic2.SetOpenCL(OpenCL);
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| //---
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| Actor.getResults(Result);
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| if(Result.Total() != NActions)
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| {
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| PrintFormat("The scope of the actor does not match the actions count (%d <> %d)", NActions, Result.Total());
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| return INIT_FAILED;
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| }
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| //---
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| Actor.GetLayerOutput(0, Result);
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| if(Result.Total() != (HistoryBars * BarDescr))
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| {
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| PrintFormat("Input size of Actor doesn't match state description (%d <> %d)", Result.Total(), (HistoryBars * BarDescr));
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| return INIT_FAILED;
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| }
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| //---
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| Actor.GetLayerOutput(LatentLayer, Result);
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| int latent_state = Result.Total();
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| Critic1.GetLayerOutput(0, Result);
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| if(Result.Total() != latent_state)
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| {
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| PrintFormat("Input size of Critic doesn't match latent state Actor (%d <> %d)", Result.Total(), latent_state);
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| return INIT_FAILED;
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| }
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| //---
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| Gradient.BufferInit(AccountDescr, 0);
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| //---
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| if(!EventChartCustom(ChartID(), 1, 0, 0, "Init"))
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| {
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| PrintFormat("Error of create study event: %d", GetLastError());
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| return INIT_FAILED;
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| }
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| //---
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| return(INIT_SUCCEEDED);
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| }
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| //+------------------------------------------------------------------+
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| //| Expert deinitialization function |
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| //+------------------------------------------------------------------+
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| void OnDeinit(const int reason)
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| {
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| //---
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| TargetCritic1.WeightsUpdate(GetPointer(Critic1), Tau);
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| TargetCritic2.WeightsUpdate(GetPointer(Critic2), Tau);
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| Actor.Save(FileName + "Act.nnw", 0, 0, 0, TimeCurrent(), true);
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| TargetCritic1.Save(FileName + "Crt1.nnw", TargetCritic1.getRecentAverageError(), 0, 0, TimeCurrent(), true);
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| TargetCritic2.Save(FileName + "Crt2.nnw", TargetCritic2.getRecentAverageError(), 0, 0, TimeCurrent(), true);
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| delete Result;
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| }
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| //+------------------------------------------------------------------+
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| //| ChartEvent function |
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| //+------------------------------------------------------------------+
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| void OnChartEvent(const int id,
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| const long &lparam,
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| const double &dparam,
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| const string &sparam)
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| {
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| //---
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| if(id == 1001)
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| Train();
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| }
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| //+------------------------------------------------------------------+
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| //| Train function |
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| //+------------------------------------------------------------------+
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| void Train(void)
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| {
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| int total_tr = ArraySize(Buffer);
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| uint ticks = GetTickCount();
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| //---
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| for(int iter = 0; (iter < Iterations && !IsStopped()); iter ++)
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| {
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| int tr = (int)((MathRand() / 32767.0) * (total_tr - 1));
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| int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2));
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| //--- Target
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| State.AssignArray(Buffer[tr].States[i + 1].state);
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| float PrevBalance = Buffer[tr].States[i].account[0];
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| float PrevEquity = Buffer[tr].States[i].account[1];
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| Account.Clear();
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| Account.Add((Buffer[tr].States[i + 1].account[0] - PrevBalance) / PrevBalance);
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| Account.Add(Buffer[tr].States[i + 1].account[1] / PrevBalance);
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| Account.Add((Buffer[tr].States[i + 1].account[1] - PrevEquity) / PrevEquity);
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| Account.Add(Buffer[tr].States[i + 1].account[2]);
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| Account.Add(Buffer[tr].States[i + 1].account[3]);
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| Account.Add(Buffer[tr].States[i + 1].account[4] / PrevBalance);
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| Account.Add(Buffer[tr].States[i + 1].account[5] / PrevBalance);
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| Account.Add(Buffer[tr].States[i + 1].account[6] / PrevBalance);
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| double x = (double)Buffer[tr].States[i + 1].account[7] / (double)(D'2024.01.01' - D'2023.01.01');
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| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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| x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_MN1);
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| Account.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
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| x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_W1);
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| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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| x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_D1);
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| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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| //---
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| if(Account.GetIndex() >= 0)
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| Account.BufferWrite();
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| if(!Actor.feedForward(GetPointer(State), 1, false, GetPointer(Account)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| ExpertRemove();
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| break;
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| }
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| //---
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| if(!TargetCritic1.feedForward(GetPointer(Actor), LatentLayer, GetPointer(Actor)) ||
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| !TargetCritic2.feedForward(GetPointer(Actor), LatentLayer, GetPointer(Actor)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| vector<float> log_prob;
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| if(!Actor.GetLogProbs(log_prob))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| TargetCritic1.getResults(Result);
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| float reward = Result[0];
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| TargetCritic2.getResults(Result);
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| reward = Buffer[tr].Revards[i] + DiscFactor * (MathMin(reward, Result[0]) - Buffer[tr].Revards[i + 1]);
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| float log_prob_forecast = DiscFactor * LogProbMultiplier * log_prob.Sum() / (float)PrevBalance;
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| //--- Q-function study
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| State.AssignArray(Buffer[tr].States[i].state);
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| PrevBalance = Buffer[tr].States[MathMax(i - 1, 0)].account[0];
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| PrevEquity = Buffer[tr].States[MathMax(i - 1, 0)].account[1];
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| Account.Update(0, (Buffer[tr].States[i].account[0] - PrevBalance) / PrevBalance);
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| Account.Update(1, Buffer[tr].States[i].account[1] / PrevBalance);
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| Account.Update(2, (Buffer[tr].States[i].account[1] - PrevEquity) / PrevEquity);
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| Account.Update(3, Buffer[tr].States[i].account[2]);
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| Account.Update(4, Buffer[tr].States[i].account[3]);
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| Account.Update(5, Buffer[tr].States[i].account[4] / PrevBalance);
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| Account.Update(6, Buffer[tr].States[i].account[5] / PrevBalance);
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| Account.Update(7, Buffer[tr].States[i].account[6] / PrevBalance);
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| x = (double)Buffer[tr].States[i].account[7] / (double)(D'2024.01.01' - D'2023.01.01');
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| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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| x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_MN1);
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| Account.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
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| x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_W1);
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| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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| x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_D1);
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| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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| Account.BufferWrite();
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| //---
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| if(!Actor.feedForward(GetPointer(State), 1, false, GetPointer(Account)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| //---
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| Actions.AssignArray(Buffer[tr].States[i].action);
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| if(Actions.GetIndex() >= 0)
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| Actions.BufferWrite();
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| //---
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| if((iter % 2) == 0)
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| {
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| if(!Critic1.feedForward(GetPointer(Actor), LatentLayer, GetPointer(Actor)) ||
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| !Critic2.feedForward(GetPointer(Actor), LatentLayer, GetPointer(Actions)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| Critic1.getResults(Result);
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| Actor.GetLogProbs(log_prob);
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| Result.Update(0, reward + LogProbMultiplier * log_prob.Sum() / (float)PrevBalance + log_prob_forecast);
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| Critic1.TrainMode(false);
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| if(!Critic1.backProp(Result, GetPointer(Actor)) ||
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| !Critic1.AlphasGradient(GetPointer(Actor)) ||
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| !Actor.backPropGradient(GetPointer(Account), GetPointer(Gradient), LatentLayer) ||
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| !Actor.backPropGradient(GetPointer(Account), GetPointer(Gradient)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| Critic1.TrainMode(true);
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| break;
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| }
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| Critic1.TrainMode(true);
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| Result.Update(0, reward);
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| if(!Critic2.backProp(Result, GetPointer(Actions), GetPointer(Gradient)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| //--- Update Target Nets
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| TargetCritic2.WeightsUpdate(GetPointer(Critic2), Tau);
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| }
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| else
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| {
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| if(!Critic1.feedForward(GetPointer(Actor), LatentLayer, GetPointer(Actor)) ||
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| !Critic2.feedForward(GetPointer(Actor), LatentLayer, GetPointer(Actions)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| Critic2.getResults(Result);
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| Actor.GetLogProbs(log_prob);
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| Result.Update(0, reward + LogProbMultiplier * log_prob.Sum() / (float)PrevBalance + log_prob_forecast);
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| Critic2.TrainMode(false);
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| if(!Critic2.backProp(Result, GetPointer(Actor)) ||
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| !Critic2.AlphasGradient(GetPointer(Actor)) ||
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| !Actor.backPropGradient(GetPointer(Account), GetPointer(Gradient), LatentLayer) ||
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| !Actor.backPropGradient(GetPointer(Account), GetPointer(Gradient)))
|
| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| Critic2.TrainMode(true);
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| break;
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| }
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| Critic2.TrainMode(true);
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| Result.Update(0, reward);
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| if(!Critic1.backProp(Result, GetPointer(Actions), GetPointer(Gradient)))
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| {
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| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| break;
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| }
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| //--- Update Target Nets
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| TargetCritic1.WeightsUpdate(GetPointer(Critic1), Tau);
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| }
|
| //---
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| if(GetTickCount() - ticks > 500)
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| {
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| string str = StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic1", iter * 100.0 / (double)(Iterations), Critic1.getRecentAverageError());
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| str += StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic2", iter * 100.0 / (double)(Iterations), Critic2.getRecentAverageError());
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| Comment(str);
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| ticks = GetTickCount();
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| }
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| }
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| Comment("");
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| //---
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| PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic1", Critic1.getRecentAverageError());
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| PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic2", Critic2.getRecentAverageError());
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| ExpertRemove();
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| //---
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| }
|
| //+------------------------------------------------------------------+
|
|
|