rlR: (Deep) Reinforcement learning in R
Installation
R package installation
devtools::install_github("smilesun/rlR")or
devtools::install_github("smilesun/rlR", dependencies = TRUE)Python dependency
rlR use keras with tensorflow as its backend for neural network as functional approximator and OpenAI gym.
see Python Dependencies Installation and Configuration
Example of Neural Network as Functional Approximator
Choose an environment to learn
library(rlR)
env = makeGymEnv("CartPole-v0")
env##
## action cnt: 2
## state original dim: 4
## discrete action
If you have R package "imager" installed, you could get a snapshot of the environment by
env$snapshot(preprocess = F)Initialize agent with the environment
agent = initAgent("AgentDQN", env)
agent$learn(200L) Look at the performance
agent$plotPerf(F)