binaryRL (version 0.9.8)

func_logl: Function: Loss Function

Description

This loss function reflects the similarity between human choices and RL model predictions. If a human selects the left option and the RL model predicts a high probability for the left option, then \(logP_{L}\) approaches 0, causing the first term to approach 0.

Since the human chose the left option, \(B_{R}\) becomes 0, making the second term naturally zero. Therefore, the more consistent the RL model's prediction is with human choice, the closer this LL value is to 0. Conversely, it approaches negative infinity. $$ LL = \sum B_{L} \times \log P_{L} + \sum B_{R} \times \log P_{R} $$

Usage

func_logl(
  i,
  L_freq,
  R_freq,
  L_pick,
  R_pick,
  L_value,
  R_value,
  L_dir,
  R_dir,
  L_prob,
  R_prob,
  var1 = NA,
  var2 = NA,
  LR,
  try,
  value,
  utility,
  reward,
  occurrence,
  alpha,
  beta
)

Value

log-likelihood

Arguments

i

The current row number.

L_freq

The frequency of left option appearance

R_freq

The frequency of right option appearance

L_pick

The number of times left option was picked

R_pick

The number of times left option was picked

L_value

The value of the left option

R_value

The value of the right option

L_dir

Whether the participant chose the left option.

R_dir

Whether the participant chose the right option.

L_prob

The probability that the model assigns to choosing the left option.

R_prob

The probability that the model assigns to choosing the left option.

var1

[character] Column name of extra variable 1. If your model uses more than just reward and expected value, and you need other information, such as whether the choice frame is Gain or Loss, then you can input the 'Frame' column as var1 into the model.

default: var1 = "Extra_Var1"

var2

[character] Column name of extra variable 2. If one additional variable, var1, does not meet your needs, you can add another additional variable, var2, into your model.

default: var2 = "Extra_Var2"

LR

Are you calculating the probability for the left option or the right option?

try

If the choice was random, the value is 1; If the choice was based on value, the value is 0.

value

The expected value of the stimulus in the subject's mind at this point in time.

utility

The subjective value that the subject assigns to the objective reward.

reward

The objective reward received by the subject after selecting a stimulus.

occurrence

The number of times the same stimulus has been chosen.

alpha

[vector] Extra parameters that may be used in functions.

beta

[vector] Extra parameters that may be used in functions.

Examples

if (FALSE) {
func_logl <- function(
  # Trial number
  i,
  # Number of times this option has appeared
  L_freq,
  R_freq,
  # Number of times this option has been chosen
  L_pick,
  R_pick,
  # Current value of this option
  L_value,
  R_value,
  # 
  L_dir,
  R_dir,
  #
  L_prob,
  R_prob,
  # Extra variables
  var1 = NA,
  var2 = NA,

  # Whether calculating probability for left or right choice
  LR,
  # Is it a random choosing trial?
  try,

  # Extra parameters
  alpha,
  beta
){
  logl <- switch(
    EXPR = LR,
    "L" = L_dir * log(L_prob),
    "R" = R_dir * log(R_prob)
  )
}
}