reinforcelearn (version 0.2.1)

Environment: Custom Reinforcement Learning Environment

Description

Custom Reinforcement Learning Environment

Arguments

step

[function(self, action)] Custom step function.

reset

[function(self)] Custom reset function.

visualize

[function(self)] Optional custom visualization function.

discount

[numeric(1) in (0, 1)] Discount factor.

action.names

[named integer] Optional action names for a discrete action space.

Usage

makeEnvironment("custom", step, reset, visualize = NULL, discount = 1, action.names = NULL)

Methods

• $step(action) Take action in environment. Returns a list with state, reward, done.

• $reset() Resets the done flag of the environment and returns an initial state. Useful when starting a new episode.

• $visualize() Visualizes the environment (if there is a visualization function).

Examples

# NOT RUN {
step = function(self, action) {
  state = list(mean = action + rnorm(1), sd = runif(1))
  reward = rnorm(1, state[[1]], state[[2]])
  done = FALSE
  list(state, reward, done)
}

reset = function(self) {
  state = list(mean = 0, sd = 1)
  state
}

env = makeEnvironment(step = step, reset = reset)
env$reset()
env$step(100)
# }