Further assessment of a model of changeover behavior: Implications for the matching law
Let the matching-law sensitivity parameter bend with overall reinforcement rate and your choice predictions stay accurate.
01Research in Context
What this study did
Avellaneda and colleagues ran a new concurrent VI procedure with rats.
They let the matching-law sensitivity parameter move up or down as overall reinforcement rate changed.
The goal was to see if a flexible rule predicts choice better than the old fixed version.
What they found
The updated model fit the rats’ data more closely than the classic matching law.
When overall reinforcement sped up, sensitivity shifted, keeping choice ratios in line.
How this fits with other research
Reid et al. (1983) already showed that local reinforcement rates guide changeovers.
The new study keeps that idea but adds a switch-cost term, so it builds on, not breaks, the 1983 review.
Rojahn et al. (2012) blended rate and magnitude into one equation; Avellaneda et al. (2025) instead let the exponent itself drift with rate, a different kind of upgrade.
Hoch et al. (2007) used plain matching to track why kids with IDD seek staff attention.
The 2025 rate-sensitive version could sharpen those natural-setting predictions when attention density swings.
Why it matters
If you track client choice across activities or staff members, remember that sensitivity can slide when reinforcement speeds up or slows down.
Try plotting choice versus reinforcement rate session-by-session; if the fit drifts, allow the slope to change instead of hunting for new reinforcers.
A moving sensitivity value may give you an earlier heads-up that the contingency is wearing thin.
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02At a glance
03Original abstract
Choice in concurrent schedules is organized in visits to each alternative, and the duration of these visits is exponentially distributed. A model of changeover behavior based on this fact successfully described changeover behavior in two large datasets from published experiments, but some limitations were apparent in this analysis, seemingly reflecting an effect of the passage of time on the data across the lengthy experiments. This paper describes an experiment that exposed rats to a dynamic concurrent variable-interval procedure designed to address these limitations. One of 35 possible combinations of overall and relative reinforcement rates was chosen pseudorandomly at the beginning of each session without signaling the specific combination in effect. By allowing the sensitivity parameter in the generalized matching law to be a function of the overall reinforcement rate, the model provided a satisfactory description of the results. This modification includes free parameters that presumably reflect the effects of how discriminable the alternatives are and how costly it is to switch between them, increasing the scope of the matching law. The updated model holds promise as the foundation for a general theory of performance in concurrent schedules of reinforcement.
Journal of the Experimental Analysis of Behavior, 2025 · doi:10.1002/jeab.70064