Against matching theory: Predictions of an evolutionary theory of behavior dynamics

McDowell, J. J.; Calvin, Olivia L.

doi:10.1016/j.beproc.2015.02.007

Cited by 17 publications

(21 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…AOs animated by the ETBD exhibit behavior on single random interval (RI) schedules of reinforcement that conforms at equilibrium to the generalized hyperbola (McDowell, ),

B = \frac{b r^{a}}{r^{a} + c},

where B represents response rate, r represents reinforcement rate, and a , b , and c are parameters of the equation (McDowell, ; McDowell & Calvin, ; McDowell & Caron, ). It is well known that the behavior of live organisms working on single variable‐interval (VI) schedules conforms at equilibrium to this equation (de Villiers, ; evidence when a ≠ 1 is reviewed by McDowell, 2013a, pp.…”

Section: Evidence Supporting the Evolutionary Theorymentioning

confidence: 99%

“…AOs animated by the theory exhibit absolute response rates in each component of a concurrent RI RI schedule that at equilibrium conform to

B_{1} = \frac{b_{1} r_{1}^{a}}{r_{1}^{a} + \frac{c_{1}}{c_{2}} r_{2}^{a} + c_{1}},

and

B_{2} = \frac{b_{2} r_{2}^{a}}{\frac{c_{2}}{c_{1}} r_{1}^{a} + r_{2}^{a} + c_{2}},

where the numerical subscripts refer to the two alternatives of the schedule, and a , the b s, and the c s are parameters of the equations (McDowell, 2013b; McDowell & Calvin, ; McDowell & Popa, ). Note that Equations and are functions of two variables, r 1 and r 2 , which means that they describe surfaces in three‐dimensional coordinate systems.…”

Section: Evidence Supporting the Evolutionary Theorymentioning

confidence: 99%

“…But they are predictions of empirical results that in many cases are already well known. A second‐stage prediction refers to a prediction for which adequate data to test the prediction do not exist or, in a few cases, where such data do exist but have not been analyzed in a way that permits an effective test of the prediction (McDowell & Calvin, ; von Neumann & Morgenstern, 1944/, pp. 7‐8).…”

Section: Second‐stage Predictions Of the Evolutionary Theorymentioning

confidence: 99%

“…Consider an experiment that arranges a set of five concurrent schedules, where reinforcer magnitude varies in one component, but remains unchanged in the other. In fits of Equations to the behavior of AOs animated by the theory, where the b s are constrained to remain constant across all five schedules, or where they are constrained to be equal in the two components of each schedule (which are requirements of two versions of matching theory, McDowell, 2013a), large percentages of variance are accounted for, but statistically significant trends with moderate effect sizes are observed in the residuals (McDowell & Calvin, ). In other words, according to the ETBD, the matching theory versions of these equations are false.…”

Section: Second‐stage Predictions Of the Evolutionary Theorymentioning

confidence: 99%

See 3 more Smart Citations

On the current status of the evolutionary theory of behavior dynamics

McDowell

2019

J Exper Analysis Behavior

View full text Add to dashboard Cite

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.

show abstract

“…AOs animated by the ETBD exhibit behavior on single random interval (RI) schedules of reinforcement that conforms at equilibrium to the generalized hyperbola (McDowell, ),

B = \frac{b r^{a}}{r^{a} + c},

Section: Evidence Supporting the Evolutionary Theorymentioning

confidence: 99%

“…AOs animated by the theory exhibit absolute response rates in each component of a concurrent RI RI schedule that at equilibrium conform to

B_{1} = \frac{b_{1} r_{1}^{a}}{r_{1}^{a} + \frac{c_{1}}{c_{2}} r_{2}^{a} + c_{1}},

and

B_{2} = \frac{b_{2} r_{2}^{a}}{\frac{c_{2}}{c_{1}} r_{1}^{a} + r_{2}^{a} + c_{2}},

Section: Evidence Supporting the Evolutionary Theorymentioning

confidence: 99%

Section: Second‐stage Predictions Of the Evolutionary Theorymentioning

confidence: 99%

Section: Second‐stage Predictions Of the Evolutionary Theorymentioning

confidence: 99%

See 2 more Smart Citations

On the current status of the evolutionary theory of behavior dynamics

McDowell

2019

J Exper Analysis Behavior

View full text Add to dashboard Cite

show abstract

“…Behavior analytic theory did not begin and end in 1913, 1938, 1957, or even 2015. Indeed, theoretical work in behavior analysis is robust, challenging and laying the foundation for future research and application; for a representative sample of some excellent contemporary theoretical work see the following (Hayes, 2013;Hughes & Barnes-Holmes, 2016;McDowell & Calvin, 2015;Nevin & Shahan, 2011).…”

mentioning

confidence: 99%

Editorial: a Very Special Issue

Hantula

2016

BEHAV ANALYST

View full text Add to dashboard Cite

Application of the evolutionary theory of behavior dynamics to severe challenging behavior

Hagopian,

Falligant

2023

J of App Behav Analysis

View full text Add to dashboard Cite

The evolutionary theory of behavior dynamics (ETBD) is a genetic algorithm that applies the Darwinian principles of evolutionary biology to model how behavior changes dynamically via selection by contingencies of reinforcement. The ETBD is a complexity theory where low‐level rules of selection, reproduction, and mutation operate iteratively to animate “artificial organisms” that generate emergent outcomes. Numerous studies have demonstrated the ETBD can accurately model behavior of live animals in the laboratory, and it has been applied recently to model automatically maintained self‐injury. The purpose of the current series of studies was to further extend the application of the ETBD to model additional functional classes of challenging behavior and clinical procedures. Outcomes obtained with artificial organisms generally corresponded well with outcomes observed with clinical cases sourced from consecutive controlled case series studies. Conceptual and methodological considerations on the application of the ETBD to model challenging behavior are discussed.

show abstract

Against matching theory: Predictions of an evolutionary theory of behavior dynamics

Cited by 17 publications

References 40 publications

On the current status of the evolutionary theory of behavior dynamics

On the current status of the evolutionary theory of behavior dynamics

Editorial: a Very Special Issue

Application of the evolutionary theory of behavior dynamics to severe challenging behavior

Contact Info

Product

Resources

About