Description Arguments Usage Methods Examples
Custom Reinforcement Learning Environment
step |
[ |
reset |
[ |
visualize |
[ |
discount |
[ |
action.names |
[ |
makeEnvironment("custom", step, reset, visualize = NULL, discount = 1, action.names = NULL)
$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.
$visualize()
Visualizes the environment (if there is a visualization function).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | step = function(self, action) {
state = list(mean = action + rnorm(1), sd = runif(1))
reward = rnorm(1, state[[1]], state[[2]])
done = FALSE
list(state, reward, done)
}
reset = function(self) {
state = list(mean = 0, sd = 1)
state
}
env = makeEnvironment(step = step, reset = reset)
env$reset()
env$step(100)
|
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