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Perception & Psychophysics. 1968. Vol. 3 (1A) 5-11. Copyright 1968, Psychonomic Journals. Santa Barbara, Calif. Comparisons of some learning models for response bias in signal detection
 

Summary: Perception & Psychophysics. 1968. Vol. 3 (1A) 5-11. Copyright 1968, Psychonomic Journals. Santa Barbara, Calif.
Comparisons of some learning models for response bias in signal detection
MORTON P. FRIEDMAN, EDWARD C. CARTERETTE, LLOYD NAKATANI AND AL AHUMADA2
UNIVERSITY OF CALIFORNIA, LOS ANGELES
The effects of variations in signal probability and varying degrees of correct feedback on response bias
were studied in a yes-no auditory signal detection task. The main finding was that the bias towards saying
yes was an increasing function of the frequency of signal feedback events, but did not depend on the
correctness of the feedback. Several learning models coupled with a simple psychophysical and decision
model yielded predictions about overall biases and certain sequential statistics. Only one model, which can
be described as an "informational" model, gave a good account of both observed overall biases and
sequential statistics. This model assumes the observer's response bias is strengthened for the feedback-
reinforced response when the observer's sensory information is ambiguous or is contradicted by the
feedback information.
This report presents an empirical and theoretical analysis of the effects of informational feedback variables
and signal-presentation probabilities on response bias in a yes-no auditory detection task. The general
approach is similar to that employed by Atkinson and Kinchla (1965) for forced-choice tasks, though we
use a broader range of informational variables and theoretical models. Our primary interest is in the effects
of varying degrees of correct feedback on response bias.
The main theoretical analysis compares a number of learning models for response bias. The learning
models assume that the feedback and signal probability conditions lead to trial-by-trial bias adjustments

  

Source: Ahumada Jr., Al - Vision Science and Technology Group, Human Factors Research and Technology Division, NASA Ames Research Center

 

Collections: Engineering