Pre-asymptotic response rates as a function of the delay-of-reinforcement gradient summation for Catania’s Operant Reserve: A reply to Berg &amp; McDowell (2011)

Don, LI; Elliffe, Douglas; Hautus, Michael J.

doi:10.1016/j.beproc.2017.01.002

Cited by 1 publication

(5 citation statements)

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“…Berg and McDowell thus concluded that Catania's () implementation of COR was not suitable for modelling molar response rates on single VI schedules. However, Li, Elliffe, and Hautus () showed that the addition of an extra parameter to control the slope of the DOR allowed COR to produce sufficiently hyperbolic response rates. A critical limitation of these studies is that no attempts were made to fit COR to real data.…”

Section: Catania's Operant Reservementioning

confidence: 99%

“…A model that generates comparable event records would output responses on each alternative as well as an associated response force. Li, Elliffe, and Hautus (2017) showed that the addition of an extra parameter to control the slope of the DOR allowed COR to produce sufficiently hyperbolic response rates. A critical limitation of these studies is that no attempts were made to fit COR to real data.…”

Section: Catania's Operant Reservementioning

confidence: 99%

“…We describe only our implementation of COR here. See previous studies for the history of the model (Berg & McDowell, 2011;Catania, 2005;Li et al, 2017).…”

Section: Catania's Operant Reservementioning

confidence: 99%

“…In the previous implementations of COR (Berg & McDowell, 2011;Catania, 2005;Li et al, 2017), the reserve value was a real-valued number bounded below by the minimum reserve value and above by the maximum reserve value parameters. These were also discrete-time implementations.…”

Section: Appendix 1 Characterization Of Cor As An Exponential Distribmentioning

confidence: 99%

“…The scaling parameter was added byLi et al (2017). Earlier studies of COR did not include the scaling parameter.…”

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confidence: 99%

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The natural mathematics of behavior analysis

Don

Hautus

Elliffe

2018

J Exper Analysis Behavior

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Models that generate event records have very general scope regarding the dimensions of the target behavior that we measure. From a set of predicted event records, we can generate predictions for any dependent variable that we could compute from the event records of our subjects. In this sense, models that generate event records permit us a freely multivariate analysis. To explore this proposition, we conducted a multivariate examination of Catania's Operant Reserve on single VI schedules in transition using a Markov Chain Monte Carlo scheme for Approximate Bayesian Computation. Although we found systematic deviations between our implementation of Catania's Operant Reserve and our observed data (e.g., mismatches in the shape of the interresponse time distributions), the general approach that we have demonstrated represents an avenue for modelling behavior that transcends the typical constraints of algebraic models.

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Section: Catania's Operant Reservementioning

confidence: 99%

Section: Catania's Operant Reservementioning

confidence: 99%

“…We describe only our implementation of COR here. See previous studies for the history of the model (Berg & McDowell, 2011;Catania, 2005;Li et al, 2017).…”

Section: Catania's Operant Reservementioning

confidence: 99%

Section: Appendix 1 Characterization Of Cor As An Exponential Distribmentioning

confidence: 99%

“…The scaling parameter was added byLi et al (2017). Earlier studies of COR did not include the scaling parameter.…”

mentioning

confidence: 99%

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