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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

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Published on: June 3, 2013

The generalization-across-dimensions model applied to conditional temporal discrimination.

Michael Davison¹, Sarah Cowie¹

¹The University of Auckland, Aotearoa, New Zealand.

Journal of the Experimental Analysis of Behavior

|April 17, 2024

Summary

This summary is machine-generated.

Recent quantitative models can explain choice behavior in conditional discrimination tasks. However, model parameters from one experiment did not predict another due to differing reinforcer control, highlighting the need for further research.

Keywords:

choice conditional discrimination generalization location control quantitative modeling temporal control

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Area of Science:

Behavioral psychology
Quantitative modeling
Animal cognition

Background:

Recent quantitative models integrate stimulus and reinforcer control.
Understanding choice behavior in conditional discrimination is crucial.

Purpose of the Study:

To test if recent quantitative models can account for choice behavior under conditional discrimination.
To investigate the influence of stimulus and reinforcer control on choice.

Main Methods:

Two experiments utilized blackout durations as conditional stimuli signaling food availability.
Varied distributions of blackout durations across sets and conditions.
Applied an updated generalization-across-dimensions model to analyze choice data.

Main Results:

The model accurately described choice changes across durations in Experiment 1.
Model parameters from Experiment 1 did not predict Experiment 2 choice.
The model still fitted Experiment 2 data well, despite parameter prediction failure.

Conclusions:

The generalization-across-dimensions model extends to conditional discrimination procedures.
Differential control by reinforcer location varied between experiments, impacting predictive accuracy.
Further research is required to elucidate the reasons for differing reinforcer control.