determineSpeakerPostListPrefsSimpleRSAWithPriorPref_indep_pr: Determine speaker's inference of the posterior listener...

In CognitiveModeling/priorinference_iterative: Prior Inference Iterative

Description

Simple RSA (iterative, independent of trial order (prior rate))

This function calculates the speaker's posterior guess of the feature value preferences of the listener in the iterative setting. That means how the speaker infers the preferences of the listener based on the object choice.

Usage

determineSpeakerPostListPrefsSimpleRSAWithPriorPref_indep_pr(
  currentObjects,
  featureUtt,
  softPrefValue,
  notObeyInst,
  priorPrefAll,
  priorRate
)

Arguments

currentObjects	A vector of three values in {1,...,27} specifying the target and the other two objects in the scene. The target is the first object in the vector (index = 1).
featureUtt	One of the values {1,2,3} specifying which feature is uttered (i.e. shape = 1 / texture = 2 / or color = 3).
softPrefValue	A parameter value between [0,infinity) (The larger the higher the tendency towards uniform liking). Value reflects how categorical the listener's preferences are: 0: The listener always picks her preferred object. If the listener prefers red objects, she will always pick the red object in the scene. infinity: It is as likely for the listener to pick green, blue or red objects.
notObeyInst	Determines the extent to which the instruction of the speaker is obeyed by the listener. (0 = full obedience, infinity = full instruction ignorance). Example: 0: Listener always picks red objects following the utterance "red". infinity: Listener as likely to pick green, blue or red objects even if the utterance is "red".
priorPrefAll	A vector of length 9. Probability mass over all feature values. Gives a prior preferences distribution over all (nine) feature values.
priorRate	This parameter specifies how much the prior information is weighed into the speaker's decision is weighed into the decision of the speaker regarding the feature preferences of the listener.

Value

A vector of length 9. It contains the speaker's inference of the feature value preferences of the listener independent of the trial order.

Examples

determineSpeakerPostListPrefsSimpleRSAWithPriorPref_indep_pr(currentObjects, featureUtt,
softPrefValue, notObeyInst, priorPrefAll, priorRate)

output:
[1]  6.666667e-01 6.666667e-101  3.333333e-01  0.000000e+00  0.000000e+00  0.000000e+00
[7]  0.000000e+00  0.000000e+00  0.000000e+00

CognitiveModeling/priorinference_iterative documentation built on Dec. 17, 2021, 3:01 p.m.