Cost function for one parameter optimization for the utterance choice experiments. (iterative setting) Optimizing klValueFactor. Softness and non-obedience are fixed. — SimpleRSAModelUttKLDivParamK

Simple RSA

klValueFactor is optimized.

Softness and non-obedience are fixed at 0.

SimpleRSAModelUttKLDivParamK_iterative(par, data)

Arguments

par

par	One value vector, which specifies one of three parameters to be optimized: klValueFactor: A parameter that can be negative, zero or positive: zero Don't care about learning about feature preferences of the listener positive Care about learning about feature preferences of the listener negative Trying to pick non-ambiguous utterances
data	A matrix with data rows. column structure: `[1:OC1,OC2,OC3,4:numUttOptions,6: picked utterance]` 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. 6: picked utterance The utterance picked by the participant.

One value vector, which specifies one of three parameters to be optimized:

data

A matrix with data rows.

column structure: [1:OC1,OC2,OC3,4:numUttOptions,6: picked utterance]

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.

6: picked utterance The utterance picked by the participant.

Minimized Kullback-Leibler divergence and the optimal parameters.

This is the iterative version of SimpleRSAModelUttKLDivParamK.