sampleGridSequence: Sample grid sequence

In 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

ReinforcementLearning documentation built on March 26, 2020, 7:38 p.m.