Falsification of matching theory and confirmation of an evolutionary theory of behavior dynamics in a critical experiment

Klapes

2020

Self Cite

The axiomatic principle that all behavior is choice was incorporated into a revised implementation of an evolutionary theory's account of behavior on single schedules. According to this implementation, target responding occurs in the context of background responding and reinforcement. In Phase 1 of the research, the target responding of artificial organisms (AOs) animated by the revised theory was found to be well described by an exponentiated hyperbola, the parameters of which varied as a function of the background reinforcement rate. In Phase 2, the effect of reinforcer magnitude on the target behavior of the AOs was studied. As in Phase 1, the AOs' behavior was well described by an exponentiated hyperbola, the parameters of which varied with both the target reinforcer magnitude and the background reinforcement rate. Evidence from experiments with live organisms was found to be consistent with the Phase-1 predictions of the revised theory. The Phase-2 predictions have not been tested. The revised implementation of the theory can be used to study the effects of superimposing punishment on single-schedule responding, and it may lead to the discovery of a function that relates response rate to both the rate and magnitude of reinforcement on single schedules. Key words: background reinforcement, evolutionary theory of behavior dynamics, quantitative law of effect, reinforcer magnitude Bryan Klapes https://orcid.org/0000-0002-2116-2872 We thank Cyrus Chi for calling our attention to the Wolfram (2020) article, and Steve Riley for teaching us about jackknife resampling. We also thank Cyrus Chi and Steve Riley for their helpful comments on an earlier version of this paper.

Section: Original Version Of the Etbd's Account Of Behavior On Singlementioning

confidence: 99%

All Behavior is choice: Revisiting an evolutionary theory's account of behavior on single schedules

Klapes

2020

Self Cite

“…In other words, according to the ETBD, the matching theory versions of these equations are false. In a reanalysis of data from Dallery et al (), who conducted this experiment with human participants, McDowell, Calvin, Hackett, and Klapes () found exactly this result, namely that fits of Equations accounted for large percentages of variance, but left systematic trends with moderate effect sizes in the residuals.…”

Section: Second‐stage Predictions Of the Evolutionary Theorymentioning

confidence: 68%

On the current status of the evolutionary theory of behavior dynamics

2019

The evolutionary theory of behavior dynamics is a complexity theory that instantiates the Darwinian principles of selection, reproduction, and mutation in a genetic algorithm. The algorithm is used to animate artificial organisms that behave continuously in time and can be placed in any experimental environment. The present paper is an update on the status of the theory. It includes a summary of the evidence supporting the theory, a list of the theory's untested predictions, and a discussion of how the algorithmic operations of the theory may correspond to material reality. Based on the evidence reviewed here, the evolutionary theory appears to be a strong candidate for a comprehensive theory of adaptive behavior.

“…Now let B + B e = k. We know that this equality is false (McDowell 2013a), but we also know that it nevertheless produces the right answer in the analogous derivation of the singlealternative hyperbola (McDowell & Calvin, 2015;McDowell et al, 2017). Hence, replacing B + B e in the above equation with k, and solving for B gives…”

Section: Appendixmentioning

confidence: 99%

Evolutionary theory prediction: Response rate as a joint function of reinforcement rate and reinforcer magnitude

Arashanapalli

2021

Artificial organisms (AOs) animated by an evolutionary theory of behavior dynamics (ETBD) worked on concurrent interval schedules with a standard reinforcer magnitude on 1 alternative and a range of reinforcer magnitudes on the other. The reinforcer magnitudes on the second alternative were hedonically scaled using the generalized matching law. The AOs then worked on single interval schedules that arranged various combinations of the scaled reinforcer magnitudes and a range of nominal schedule values. This produced bivariate response rate data to which 5 candidate equations were fitted. One equation was found to provide the best description of the bivariate data in terms of percentage of variance accounted for, information criterion value, and residual profile. This equation consisted of 2 factors, 1 entailing the scaled magnitude, 1 entailing the obtained reinforcement rate, and both expressed in the form of exponentiated hyperbolas. The theory's prediction of the bivariate equation, along with additional predictions of the theory, were tested on data from an experiment in which rats pressed levers for various concentrations of sucrose pellets. The bivariate equation predicted by the theory was confirmed, as were all the additional predictions of the theory that could be tested on this data set.