lazytrade (version 0.5.4)

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

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(x, states, actions, control)

Value

dataframe with log of RL model reward sequences during model update

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

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)