Steady‐state Performance on Fixed‐, Mixed‐, and Random‐ratio Schedules

Mazur, James E.

doi:10.1901/jeab.1983.39-293

Cited by 86 publications

(109 citation statements)

References 16 publications

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“…Previous studies ofIRTs and PRPs in FR schedules have reported that PRPs increase as a function of the FR, but that IRTs of less than 1 sec remain relatively constant (Felton & Lyon, 1966;Mazur, 1983). Those studies, however, were all performed in an open economy: the animals were food deprived, earned some portion of their food within a short experimental session, and were consequently returned to their home cages where supplemental food was provided.…”

Section: Discussionmentioning

confidence: 99%

“…A word of caution,however, should be addedconcerning IRTs. Although Mazur (1983), with reference to his IRT distributions, notesthat "there was no tendency for the peaks to shift toward longer IRTs as ratio size increased" (p. 297), there was an increase in "long" IRTs (lRTs greater than 1 sec) with FR size. Such long IRTs represented lessthan 10% of all IRTs in the Mazurstudy, and it is probably true that the median IRT, as a resistant measureof centraltendency (Hartwig & Dearing, 1979), wouldbe relatively unaffectedby longIRTs in the present study.…”

Section: Demand Curvesmentioning

confidence: 97%

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Rapid demand curves for behavioral economics

Raslear

Bauman

Hursh

et al. 1988

Animal Learning & Behavior

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A method for determining the relationship between food consumption and the price of food (demand function) in behavioral economic experiments is described. Although previous methods have generally required as long as 40 days, the present method can generate a complete demand function within 7 days, and therefore may be more suitable for use in the evaluation of drugs, toxins, and physiological/anatomical interventions. Moreover, measures of circadian rhythmicity, postreinforcement pause durations, and interresponse times can also be generated. Three experiments tested the stability of the method in a variety of procedural manipulations: repeated exposure to the procedure, increasing versus random daily food price, and size of daily changes in food price. The procedure generated demand functions that were similar to those that require more extended testing, and the demand functions were not generally affected by procedural manipulations. Body weight, which can also affect consumption, generally decreases with increases in the price of food; so this variable should be recorded and used as a covariate in analyzing demand functions. With the exception of circadian rhythmicity, the other measures were stable across procedural variations and showed expected changes as a function of food price: postreinforcement pause durations increased as price increased, but interresponse times did not.Recently a great deal of interest has focused on the application of economic principles to the analysis of behavioral data generated by animal subjects (Allison, 1983;Hursh, 1980Hursh, , 1984. A primary task for such an analysis is the generation of a function that relates the price of a commodity (e.g., the number of responses required to obtain a 45-mg food pellet) to the quantity of the commodity that is consumed. Functions that relate quantity consumed to price are known in economics as demand curves, and Figure 1 illustrates the features of demand curves that are commonly seen in the behavioral literature. Assume that the subjects earn all of their food within the experimental apparatus by performing a specified response, and that the delivery of food pellets is contingent upon production of a fixed number of responses (i.e., a fixed ratio, or FR, schedule of reinforcement). Price (P), then, is measured in responses per pellet, as indicated along the abscissa of Figure 1. The quantity consumed (Q), measured in pellets of food, is plotted on the ordinate. Note that the ordinate and abscissa are both logarithmic. A demand curve, such as A in Figure 1, is generated by changing the price of the commodity and measuring the quantity of the commodity that is then consumed. Demand elasticity is defined as the percentage change in consump- tion per percentage change in price (%i1Q/%M7). In double logarithmic plots, the slope of the demand curve can be directly read as elasticity. Unit elasticity is depicted in curve B, since a 1% change in price produces a 1% change in consumption (i.e., slope = -1). Inelastic demand is illustrated in cur...

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Section: Discussionmentioning

confidence: 99%

Section: Demand Curvesmentioning

confidence: 97%

Rapid demand curves for behavioral economics

Raslear

Bauman

Hursh

et al. 1988

Animal Learning & Behavior

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“…Equation 3 provides a good account of the behavior of pigeons on ratio schedules, both on VR schedules with the coupling coefficient defined by Equation 2 (e.g., Green, Kagel, & Battalio, 1982;Mazur, 1983), and on fixed-ratio (FR) schedules (e.g., Powell, 1968) using the appropriate coupling coefficient. In particular, changes in the amount or quality of the reinforcer have the expected effects on both the shape of the response rate functions and on the corresponding values of a (see Figure 2, from Bizo & Killeen, 1997).…”

Section: Model and Predictionsmentioning

confidence: 99%

Rats don’t always respond faster for more food: The paradoxical incentive effect

Bizo

Kettle

Killeen

2001

Animal Learning & Behavior

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Rats' leverpressing was reinforced on variable-ratio (VR) schedules. As ratio values increased, response rates initially increased with them, then eventually decreased. In Experiment 1, rates were uniformly higher with one-pellet reinforcers than with two-pellet reinforcers-the paradoxical incentive effect. Killeen's (1994) mathematical principles of reinforcement (MPR) described the data quantitatively but failed to predict the advantage for the one-pellet condition. In Experiment 2, rats receivedone-, two-, and three-pellet reinforcers with counterbalanced preloads of pellets; the continued superiority of the smaller reinforcers ruled out a satiation explanation. Experiment 3 introduced a 20-sec intertrial interval (ITI), and Experiment 4 filled the ITI with an alternate response to test a memorial/overshadowing explanation. In Experiment 5, the rats received one or two standard grain pellets or one sucrose pellet as reinforcers over an extended range of ratios. Once again, rates were higher for one than for two pellets at short to moderate VR values; thereafter, two pellets supported higher response rates. The diminution of the effect in Experiment 3 and its reversal in Experiment 4 and in Experiment 5 at large ratios provided evidence for overshadowing and reconciled the phenomenon with MPR.

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“…The FR variable most often investigated is ratio size. As FR size increases, the length of the postreinforcement (sometimes called preratio) pause (PRP) also increases whether pigeons (Felton & Lyon, 1966;Powell, 1968) or rats (Mazur, 1983) are subjects. Response rates, as a function of this same parameter, also have been reported.…”

mentioning

confidence: 99%

“…It is more difficult to locate studies that have manipulated ratio size in variable-ratio (VR) or random-ratio (RR) schedules, as Mazur (1983) has indicated. Priddle-Higson, Lowe, and Harzem (1976) examined changes in reinforcer magnitude and changes in VR size.…”

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confidence: 99%

A Comparison of Response Patterns on Fixed‐, Variable‐, and Random‐ratio Schedules

Crossman

Bonem

Phelps

1987

J Exper Analysis Behavior

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The behavior of individual pigeons on fixed-ratio, variable-ratio, and random-ratio schedules was examined. Within each type of ratio schedule the size of the ratio was varied in an irregular sequence. At various ratio sizes (5, 10, 40, 80) no differences were found among overall response rates (postreinforcement pause plus running response rate) as a function of ratio type. This similarity in overall response rates held despite noticeable differences in the microstructure of performance both within and across subjects; the primary performance difference on the three types of ratio schedules was the relatively longer postreinforcement pause duration on the fixed-ratio schedule. We concluded that the gross temporal characteristics of performance determined by the relative weightings of the postreinforcement pause and running response rate were primarily controlled by the type of ratio schedule (fixed, variable, or random), whereas the overall rate of responding was controlled by the size of the ratio.

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Steady‐state Performance on Fixed‐, Mixed‐, and Random‐ratio Schedules

Cited by 86 publications

References 16 publications

Rapid demand curves for behavioral economics

Rapid demand curves for behavioral economics

Rats don’t always respond faster for more food: The paradoxical incentive effect

A Comparison of Response Patterns on Fixed‐, Variable‐, and Random‐ratio Schedules

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