Local rates of responding and reinforcement during concurrent schedules

The generalized matching law as a description of multiple-schedule responding

The literature was examined to determine how well the generalized matching law (Baum, 1974) describes multiple-schedule responding. In general, it describes the data well, accounting for a median of 91% of the variance. The median size of the undermatching parameter was 0.46; the median bias parameter was 1.00. The size of the undermatching parameter, and the proportion of the variance accounted for by the equation, varied inversely with the number of schedules conducted, with the number of sessions conducted per schedule, and with the time within a component. The undermatching parameter also varied with the operanda used to produce reinforcers and with the reinforcer used. The undermatching parameter did not vary consistently with component duration or with several other variables. Bias was greater when fewer rather than more schedules were conducted, when two rather than one operanda were used, and when White Carneaux rather than homing pigeons served as subjects. These results imply that the generalized matching law may describe both concurrent and multiple-schedule responding, but that the same variables do not always influence the bias and undermatching parameters in the same way for the two types of schedules.

Choice in transition: A comparison of melioration and the kinetic model

Transition-state choice behavior of pigeons was examined in two experiments designed to test predictions of melioration and the kinetic model. Both experiments began with an initial training condition during which subjects were maintained on concurrent variable-interval schedules. In Experiment 1, subjects were then exposed to concurrent variable-ratio schedules, whereas in Experiment 2, subjects were then exposed to concurrent extinction. Contrary to the predictions of melioration, but consistent with the kinetic model, acquisition of preference on concurrent variable-ratio schedules followed a negatively accelerated logistic trajectory, and preference remained stable in concurrent extinction. Predictions made by the kinetic model concerning rates of switching between alternatives were also supported.

Determinants of human performance on concurrent schedules

Six experiments, each with 5 human adults, were conducted to investigate the determinants of human performance on multiple concurrent variable-interval schedules. A two-key procedure was employed in which subjects' key presses produced points exchangeable for money. Variables manipulated across experiments were (a) changeover delay (Experiments 2, 4, and 6), (b) ordinal cues related to scheduled reinforcement frequencies (Experiments 3 and 4), and (c) instructions describing the ordinal relations between schedule-correlated stimuli and scheduled reinforcement frequency (Experiments 5 and 6). The performances of only 13 of the 30 subjects could be described by the generalized matching equation and were within a range of values typical of those reported in the animal literature. Eight subjects showed indifference, 9 undermatched, 7 approximated matching, 3 overmatched, and a further 3 responded exclusively to the richer component of the concurrent schedules. These differing modes of responding were closely related to the different types of performance rules reported by subjects in postexperimental questionnaires. The results are in good agreement with those from studies of human performance on single schedules, suggesting that rule-governed behavior, in interaction with contingencies, may be an important determinant of human choice.

Choice, experience, and the generalized matching law

Five pigeons were exposed to different pairs of concurrent variable-interval, variable-interval schedules on nine experimental conditions of 30 sessions each. For every session, the parameters of the generalized matching equation were computed for the first five, six, seven, eight, and nine experimental conditions. The exponent a, both for response and time distribution, tended to decrease with increases in number of experimental conditions and to increase with number of sessions per condition, but values of k (bias) varied unsystematically. When the subjects were exposed to five new pairs of schedules, with 55 sessions per condition, the findings were confirmed. Data from the literature on the generalized matching law suggest that the variability of exponent values may be explained in part by the use of naive or experienced subjects in different investigations and by the variability in number of experimental conditions and in number of sessions per condition.