Component probability and component reinforcer rate as biasers of free-operant detection.
Reinforcement rate only steers choice when the learner can already discriminate the cues; otherwise the mere chance of being in a schedule takes over.
01Research in Context
What this study did
The team ran pigeons in a two-key signal-detection task. Each daily session had two kinds of components: one where the keys looked different and one where they looked the same.
Within each component the birds could earn food at different speeds. The authors then asked: does the bird’s bias come from (a) how often that component shows up, or (b) how fast the grain arrives inside it?
What they found
When the keys were easy to tell apart, bias tracked the grain rate inside that component. When the keys looked alike, bias flipped and followed how likely the whole component was to appear.
Discrimination itself stayed high with different stimuli and stayed low with identical stimuli—reinforcement only moved the birds’ preference, not their ability to see the difference.
How this fits with other research
Gentry et al. (1980) and Rapport et al. (1982) already showed that changing payoff shifts bias without touching sensitivity. Malouff et al. (1985) keep that story but add the twist: the same payoff matters only if the bird can already tell the stimuli apart.
Gulley et al. (1997) later moved the idea to humans with ID in a matching task and got the same rate-driven bias, proving the rule works outside pigeons.
LeBlanc et al. (2003) seem to clash by saying richer schedules also make discrimination more resistant to disruption. The studies don’t disagree—M et al. kept discriminability fixed while A et al. measured how strength grows over time.
Why it matters
You now have a quick rule: if the learner can already tell the SD from S-delta, raise the within-task reinforcement rate to pull responding toward it. If the stimuli look too similar, first improve discrimination; otherwise the schedule probability, not your reinforcer speed, will drive the bias. Check your teaching materials—are the cues easy to tell apart? If not, fix the stimuli before you crank up the tokens.
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02At a glance
03Original abstract
Six pigeons were trained on multiple schedules whose components were concurrent variable-interval extinction and concurrent extinction variable-interval schedules. In Experiments 1a and 1b the stimuli signaling the components were two different light intensities, and in Experiments 2a and 2b they were two identical intensities. The components of the multiple schedule changed probabilistically after each reinforcer. In Experiments 1a and 2a, the probability of presenting the components was varied over five conditions and a replication. In Experiments 1b and 2b, the component probability was .5 and the component reinforcer rates were varied systematically over five conditions and a replication. The data, analyzed according to the Davison-Tustin behavioral detection model, confirmed that the discriminability of the stimuli signaling the components was high when the stimuli were different, and low when the stimuli were the same. Discriminability, measured by log d, was unaffected by component probability variation and by component reinforcer-rate variation. When discriminability was high, bias, or the response allocation between the two keys, was more strongly affected by variation of reinforcer rate within components than by variation of component probability, but the reverse was found when discriminability was low. The results suggest that free-operant detection performance is controlled by the rates of reinforcers in periods of time in which stimuli signal differential contingencies. These periods comprise the components when the component stimuli are discriminable, and comprise the total session when the components are indiscriminable. An extension of the Davison-Tustin behavioral detection model that incorporates these results is presented.
Journal of the experimental analysis of behavior, 1985 · doi:10.1901/jeab.1985.44-103