rl_log_progress function

Function to retrieve and help to log Q values during RL progress.

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

rl_log_progress(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

Returns

dataframe with log of RL model reward sequences during model update

Examples

# retrieve RL model Q values progress
library(ReinforcementLearning)
library(dplyr)
library(magrittr)
library(lazytrade)
data(data_trades)
x <- data_trades
states <- c("tradewin", "tradeloss")
actions <- c("ON", "OFF")
control <- list(alpha = 0.7, gamma = 0.3, epsilon = 0.1)

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