sampleGridSequence: Sample grid sequence

In nproellochs/ReinforcementLearning: Model-Free Reinforcement Learning

Description

Function uses an environment function to generate sample experience in the form of state transition tuples.

Usage

sampleGridSequence(N, actionSelection = "random", control = list(alpha
  = 0.1, gamma = 0.1, epsilon = 0.1), model = NULL, ...)

Arguments

N	Number of samples.
actionSelection	(optional) Defines the action selection mode of the reinforcement learning agent. Default: random.
control	(optional) Control parameters defining the behavior of the agent. Default: alpha = 0.1; gamma = 0.1; epsilon = 0.1.
model	(optional) Existing model of class rl. Default: NULL.
...	Additional parameters passed to function.

Value

An dataframe containing the experienced state transition tuples s,a,r,s_new. The individual columns are as follows:

State

The current state.

Action

The selected action for the current state.

Reward

The reward in the current state.

NextState

The next state.

See Also

gridworldEnvironment

ReinforcementLearning

nproellochs/ReinforcementLearning documentation built on March 3, 2020, 12:22 a.m.