rl_log_progress_mt {lazytrade}

Function to retrieve and help to log Q values during RL progress. This function is dedicated to the situations when Market Types are used as a 'states' for the Environment.

Description

Function will record Q values during the model update. These values will be used by another function Function was developed to help to estimate best control parameters during optimisation process

Usage

rl_log_progress_mt(x, states, actions, control)

Arguments

x

• dataframe containing trading results

states

• Selected states of the System

actions

• Selected actions executed under environment

control

• control parameters as defined in the Reinforcement Learning Package

Value

dataframe with log of RL model reward sequences during model update

Author(s)

(C) 2020, 2021 Vladimir Zhbanko

Examples

# retrieve RL model Q values progress
library(ReinforcementLearning)
library(dplyr)
library(magrittr)
library(lazytrade)
data(trading_systemDF)
x <- trading_systemDF
states <- c("BUN", "BUV", "BEN", "BEV", "RAN", "RAV")
actions <- c("ON", "OFF") # 'ON' and 'OFF' are referring to decision to trade with Slave system
control <- list(alpha = 0.7, gamma = 0.3, epsilon = 0.1)

rl_log_progress_mt(x = x,states = states, actions = actions, control = control)