Effects of response-allocation constraints on multiple-schedule performance.
Reinforcer rate inside each schedule chunk drives response rate even when you switch chunks by response count instead of time.
01Research in Context
What this study did
Rutter et al. (1987) worked with pigeons on two-key multiple VI schedules. The birds could earn grain on either key, but the schedule components changed in two different ways.
In one condition, the components switched after a fixed number of total responses. In the other, they switched after a fixed amount of time passed. The team kept the reinforcer rate the same inside each component.
What they found
Response rates stayed locked to the reinforcer rate inside each component. It did not matter whether the switch was triggered by response count or by a clock.
The pigeons pecked faster in the rich component and slower in the lean one, no matter how the schedule moved on.
How this fits with other research
Reiss et al. (1982) showed that shorter components can inflate response rates, but only when they are paired with higher reinforcer rates. Rutter et al. (1987) tighten the lens: even when you force a switch after a set number of responses, the reinforcer rate still rules.
McLean et al. (1983) found that extra reinforcers in other components shift both sensitivity and bias. The 1987 study keeps those extra reinforcers out and shows the core effect holds without them.
Emmelkamp et al. (1986) tracked time allocation and saw the same local response rate across conditions. The 1987 paper adds a new twist—response-based switches—but the same reinforcer-rate control appears.
Why it matters
If you run multiple schedules in practice, you can relax about how you rotate components. Use a timer, a response counter, or even learner-initiated switches—just keep the reinforcer rate steady in each piece. This frees you to pick the transition rule that best fits your client’s needs without worrying that you will warp the response rate.
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02At a glance
03Original abstract
Four pigeons were trained on multiple variable-interval schedules in which components alternated after a fixed number of responses had been emitted. In Part 1, each component change occurred after 20 responses; in Part 2, the number was 40; and in Part 3, the number of responses before change was 10. Component reinforcer rates were varied over five experimental conditions in each of Parts 1 to 3. Component response rates decreased as the specified number of responses per component was increased. However, the relation between component response-rate ratios and component reinforcer-rate ratios was independent of the specified number of responses per component, and was similar to that found when components alternate after fixed time periods. In the fourth part of the experiment, the results from Parts 1 to 3 were systematically replicated by keeping the component reinforcer rates constant, but different, while the number of responses that produced component alternation was varied from 5 to 60 responses. The results showed that multiple-schedule performance under component-response-number constraint is similar to that under conventional component-duration constraint. They further suggest that multiple-schedule response rates are controlled by component reinforcer rates and not by principles of maximizing overall reinforcer rates or meliorating component reinforcer rates.
Journal of the experimental analysis of behavior, 1987 · doi:10.1901/jeab.1987.47-29