On the form of the relation between response rates in a multiple schedule.
Response rates in multi-part sessions follow a predictable power curve tied to relative payoff.
01Research in Context
What this study did
Lattal (1974) worked with pigeons in a lab.
The birds pecked a key that switched between two fixed-interval schedules.
The team tracked how fast the birds pecked when the rate of food changed in each part.
What they found
Response speed in each part followed a simple power curve.
When one part paid off twice as much, pecks there rose by about 1.4 times, not 2.
The curve flattened at the top, showing diminishing returns.
How this fits with other research
Carmichael et al. (1999) later saw the same curve with kids choosing between two levers.
They added a change-over delay, but rate still ruled choice, matching A’s curve.
Kleinert‐Ventresca et al. (2023) and Hranchuk et al. (2019) used the same tight single-case lab style, yet looked at naming, not rates.
Together they show the power law works across species and tasks.
Why it matters
You can predict how clients will split their time across tasks once you know the payoff ratio.
No need to guess—just count reinforcers in each part, plug the ratio into the curve, and set realistic response targets.
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02At a glance
03Original abstract
Three pigeons received training on multiple variable-interval schedules with brief alternating components, concurrently with a fixed-interval schedule of food reinforcement on a second key. Fixed-interval performance exhibited typical increases in rate within the interval, and was independent of multiple-schedule responding. Responding on the multiple-schedule key decreased as a function of proximity to reinforcement on the fixed-interval key. The overall relative rate of responding in one component of the multiple schedule roughly matched the overall relative rate of reinforcement. Within the fixed interval, response rate during one multiple-schedule component was a monotonic, negatively accelerated function of response rate during the other component. To a first approximation, the data were described by a power function, where the exponent depended on the relative rate of reinforcement obtained in the two components. The relative rate of responding in one component of the multiple schedule increased as a function of proximity to fixed-interval reinforcement, and often exceeded the overall obtained relative rate of reinforcement. The form of the function relating response rates is discussed in relation to findings on rate-dependent effects of drugs, chaining, and the relation between response rate and reinforcement rate in single-schedule conditions.
Journal of the experimental analysis of behavior, 1974 · doi:10.1901/jeab.1974.21-237