Free-operant compounding of low-rate stimuli

On Response Strength and the Concept of Response Classes

Simon et al. (2020) argue that the concept of response strength is unnecessary and potentially harmful in that it misdirects behavior analysts away from more fruitful molar analyses. I defend the term as a useful summary of the effects of reinforcement and point particularly to its utility as an interpretive tool in making sense of complex human behavior under multiple control. Physiological data suggest that the concept is not an explanatory fiction, but strength cannot be simply equated with neural conductivity; interaction with competing behaviors must be considered as well. Decisions about appropriate scales of analysis require a clarification of terms. I suggest defining behavior solely in terms of its sensitivity to behavioral principles, irrespective of locus, magnitude, or observability. Furthermore, I suggest that the term response class be restricted to units that vary together in probability in part because of overlapping topography. In contrast, functional classes are united by common consequences; they vary together with respect to motivational variables but need not share formal properties and need not covary with acquisition and extinction contingencies.

Discriminated response and incentive processes in operant conditioning: a two-factor model of stimulus control

Understanding stimulus control generated in instrumental learning requires the direct investigation of discriminated response and reinforcer (incentive) processes acquired exclusively through the response-reinforcer contingencies operating on complex (multicomponent) baselines. Two series of stimulus-compounding studies accomplished this direct investigation. In one series, the independent variable was the relative reinforcement between schedule components; in the second series, it was relative response rate between components. Stimulus-compounding tests revealed that response and incentive processes enhanced each other when in agreement, counteracted each other when in opposition, and produced intermediate results when only one factor was operating. This pattern of results led to the conclusion that these factors were algebraically combining and to the development of a response/incentive matrix reflecting these dynamics. This two-factor analysis was extended to the peak-shift effect in stimulus generalization experiments and to the generation of inhibitory control. Two decades of stimulus compounding and peak-shift research were organized within this two-factor framework, extending this traditional approach to learning to active research areas heretofore not systematically considered in these terms.