Generalization of response patterns in a multiple peak procedure

Divided stimulus control depends on differential and nondifferential reinforcement: Testing a quantitative model

We investigated the effects of differential and nondifferential reinforcers on divided control by compound-stimulus dimensions. Six pigeons responded in a delayed matching-to-sample procedure in which a blue or yellow sample stimulus flashed on/off at a fast or slow rate, and subjects reported its color or alternation frequency. The dimension to report was unsignaled (Phase 1) or signaled (Phase 2). Correct responses were reinforced with a probability of .70, and the probability of reinforcers for errors varied across conditions. Comparison choice depended on reinforcer ratios for correct and incorrect responding; as the frequency of error reinforcers according to a dimension increased, control (measured by log d) by that dimension decreased and control by the other dimension increased. Davison and Nevin's (1999) model described data when the dimension to report was unsignaled, whereas model fits were poorer when it was signaled, perhaps due to carryover between conditions. We are the first to test this quantitative model of divided control with reinforcers for errors and when the dimension to report is signaled; hence, further research is needed to establish the model's generality. We question whether divided stimulus control is dimensional and suggest it may instead reflect joint control by compound stimuli and reinforcer ratios.

Generalizing from the Past, Choosing the Future

Behavior in the present depends critically on experience in similar environments in the past. Such past experience may be important in controlling behavior not because it determines the strength of a behavior, but because it allows the structure of the current environment to be detected and used. We explore a prospective-control approach to understanding simple behavior. Under this approach, order in the environment allows even simple organisms to use their personal past to respond according to the likely future. The predicted future controls behavior, and past experience forms the building blocks of the predicted future. We explore how generalization affects the use of past experience to predict and respond to the future. First, we consider how generalization across various dimensions of an event determines the degree to which the structure of the environment exerts control over behavior. Next, we explore generalization from the past to the present as the method of deciding when, where, and what to do. This prospective-control approach is measurable and testable; it builds predictions from events that have already occurred, and assumes no agency. Under this prospective-control approach, generalization is fundamental to understanding both adaptive and maladaptive behavior.