RSAModelKLDiv3params_simpleRSA4TrialsIterative_dep: Simple RSA model Kullback-Leibler divergence determination...

In CognitiveModeling/priorinference_iterative: Prior Inference Iterative

Description

Simple RSA (iterative, dependent on trial order)

The function calculates the optimal parameter values of the free parameters by estimating the log-likelihood of the RSA model given model parameters and data. It also determines the actual RSA model Kullback-Leibler divergence.

2 parameter optimization considering only the available feature values present in the scene, i.e. feature values of shape, texture and color. This function is used in the iterative dependent on the trial scenario.

Usage

RSAModelKLDiv3params_simpleRSA4TrialsIterative_dep(data, par1, par2)

Arguments

data	A matrix with data rows. column structure: [1:OC1,OC2,OC3,4:numUttOptions,7-X:TurkerSliderValues] 1:OC1 Object 1. A value between 1 and 27. 2:OC2 Object 2. A value between 1 and 27. 3:OC3 Object 3. A value between 1 and 27. 4:numUttOptions The number of valid utterances in the scene. 7-X:TurkerSliderValues These columns contain the participants' slider values.
par1	softness parameter The strength of "preferring one entity over others". (The larger the value the higher the tendency towards uniform liking)
par2	non-obedience parameter The extent to which the instruction of the speaker is obeyed by the listener. (0 = full obedience, infinity = full instruction ignorance).

Details

This function is used in LL1_1_Iterative_dep_notObey0,

LL1_1_Iterative_dep_notObey0.1,

LL1_2_Iterative_dep_pref0,

LL2_12_Iterative_dep.

Value

Minimized Kullback-Leibler divergence and the optimal parameter values.

Minimized Kullback-Leibler divergence and the optimal parameters.

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