A Critical Review of the Support for Variability as an Operant Dimension

Abstract

There is abundant evidence that behavioral variability is more predominant when reinforcement is contingent on it than when it is not, and the interpretation of direct reinforcement of variability suggested by Page and Neuringer, Journal of Experimental Psychology: Animal Behavior Processes, 11(3), 429–452 (1985) has been widely accepted. Even so, trying to identify the underlying mechanisms in the emergence of stochastic-like variability in a variability contingency is intricate. There are several challenges to characterizing variability as directly reinforced, most notably because reinforcement traditionally has been found to produce repetitive responding, but also because directly reinforced variability does not always relate to independent variables the same way as more commonly studied repetitive responding does. The challenging findings in variability experiments are discussed, along with alternative hypotheses on how variability contingencies may engender the high variability that they undeniably do. We suggest that the typical increase in behavioral variability that is often demonstrated when reinforcement is contingent on it may be better explained in terms of a dynamic interaction of reinforcement and extinction working on several specific responses rather than as directly reinforced.

Molecular (moment‐to‐moment) and molar (aggregate) analyses of behavior

“…Of great interest would be to determine how other kinds of temporal patterns produce other kinds of functions and averages. Even with the limited results available today we can see that Skinner's (1946) initial discovery with DRL and DRH contingencies that reinforcement shapes sequential structure of behavior is a very general phenomenon (Anger, 1973(Anger, /1954(Anger, , 1956Blough, 1966;Galbicka, 1997;Morse, 1966;Nevin, 1979a;Shimp, 2013Shimp, , 2014Staddon, 1968;Zeiler, 2006; and see Reed, 2007, andMacDonall, 2009 for closely related work; and see Nergaard & Holth, 2020 for a very recent and excellent review of relevant empirical and theoretical literature).…”

The unpredictable Buridan's ass: Failure to predict decisions in a trivial decision-making task

“…chaos (Hoefer, 2016). Some behaviorists have argued that variation itself is a reinforcable dimension of behavior (Nergaard & Holth, 2020). Perhaps humans as well as other animals have a specifically evolved ability to generate random numbers, to help with things like choosing a foraging location while minimizing competition or predictability by predators, even if this ability is imperfect.…”

“…In a noncompetitive version of this method, in which predictve models are trained and tested after all the data was collected, Shteingart and Loewenstein (2016) obtained about 60% accuracy with logistic regression. Broadly, the literature indicates that people fail to produce sequences that pass stringent tests of randomness (Nickerson, 2002;Nickerson & Butler, 2009), although the tests and instructions used matter (Nickerson, 2002) and with practice, people (e.g., Delogu et al, 2020) as well as animals (e.g., Nergaard & Holth, 2020) can learn to produce better random numbers.…”

Dissolving the molar–molecular controversy

“…In contrast, when C is present, A and B may become independent or so weakly dependent that the stream of IRTs will pass one or more statistical tests of randomness. In studies of operant variability, for example, Machado identified C as a strong form of negative frequency‐dependent selection (see Machado, 1989, 1992, 1993; also, Machado et al, 2008, Machado & Tonneau, 2012; Nergaard & Holth, 2020; Shimp, 1967). In this case, the stream of binary choices suggests a Bernoulli‐like process.…”