Literature DB >> 8354966

Response acquisition under targeted percentile schedules: a continuing quandary for molar models of operant behavior.

G Galbicka1, M A Kautz, T Jagers.   

Abstract

The number of responses rats made in a "run" of consecutive left-lever presses, prior to a trial-ending right-lever press, was differentiated using a targeted percentile procedure. Under the nondifferential baseline, reinforcement was provided with a probability of .33 at the end of a trial, irrespective of the run on that trial. Most of the 30 subjects made short runs under these conditions, with the mean for the group around three. A targeted percentile schedule was next used to differentiate run length around the target value of 12. The current run was reinforced if it was nearer the target than 67% of those runs in the last 24 trials that were on the same side of the target as the current run. Programming reinforcement in this way held overall reinforcement probability per trial constant at .33 while providing reinforcement differentially with respect to runs more closely approximating the target of 12. The mean run for the group under this procedure increased to approximately 10. Runs approaching the target length were acquired even though differentiated responding produced the same probability of reinforcement per trial, decreased the probability of reinforcement per response, did not increase overall reinforcement rate, and generally substantially reduced it (i.e., in only a few instances did response rate increase sufficiently to compensate for the increase in the number of responses per trial). Models of behavior predicated solely on molar reinforcement contingencies all predict that runs should remain short throughout this experiment, because such runs promote both the most frequent reinforcement and the greatest reinforcement per press. To the contrary, 29 of 30 subjects emitted runs in the vicinity of the target, driving down reinforcement rate while greatly increasing the number of presses per pellet. These results illustrate the powerful effects of local reinforcement contingencies in changing behavior, and in doing so underscore a need for more dynamic quantitative formulations of operant behavior to supplement or supplant the currently prevalent static ones.

Entities:  

Mesh:

Year:  1993        PMID: 8354966      PMCID: PMC1322153          DOI: 10.1901/jeab.1993.60-171

Source DB:  PubMed          Journal:  J Exp Anal Behav        ISSN: 0022-5002            Impact factor:   2.468


  15 in total

Review 1.  Animal cognition: the representation of space, time and number.

Authors:  C R Gallistel
Journal:  Annu Rev Psychol       Date:  1989       Impact factor: 24.137

2.  Mechanics of the animate.

Authors:  P R Killeen
Journal:  J Exp Anal Behav       Date:  1992-05       Impact factor: 2.468

3.  Applying linear systems analysis to dynamic behavior.

Authors:  J J McDowell; R Bass; R Kessel
Journal:  J Exp Anal Behav       Date:  1992-05       Impact factor: 2.468

4.  Differentiating the behavior of organisms.

Authors:  G Galbicka
Journal:  J Exp Anal Behav       Date:  1988-09       Impact factor: 2.468

5.  Reinforcement rate and interresponse time differentiation.

Authors:  D O Kuch; J R Platt
Journal:  J Exp Anal Behav       Date:  1976-11       Impact factor: 2.468

6.  Control over response number by a targeted percentile schedule: reinforcement loss and the acute effects of d-amphetamine.

Authors:  G Galbicka; K P Fowler; Z J Ritch
Journal:  J Exp Anal Behav       Date:  1991-09       Impact factor: 2.468

7.  Operant conditioning of behavioral variability using a percentile reinforcement schedule.

Authors:  A Machado
Journal:  J Exp Anal Behav       Date:  1989-09       Impact factor: 2.468

8.  Response-reinforcer contingency and spatially defined operants: testing an invariance property of phi.

Authors:  G Galbicka; J R Platt
Journal:  J Exp Anal Behav       Date:  1989-01       Impact factor: 2.468

9.  Parametric manipulation of interresponse-time contingency independent of reinforcement rate.

Authors:  G Galbicka; J R Platt
Journal:  J Exp Psychol Anim Behav Process       Date:  1986-10

10.  Motivational and response factors in temporal differentiation.

Authors:  J R Platt
Journal:  Ann N Y Acad Sci       Date:  1984       Impact factor: 5.691

View more
  7 in total

1.  Using computers to teach behavior analysis.

Authors:  E Shimoff; A C Catania
Journal:  Behav Anal       Date:  1995

2.  Shaping in the 21st century: Moving percentile schedules into applied settings.

Authors:  G Galbicka
Journal:  J Appl Behav Anal       Date:  1994

3.  Shaping academic task engagement with percentile schedules.

Authors:  Elizabeth S Athens; Timothy R Vollmer; Claire C St Peter Pipkin
Journal:  J Appl Behav Anal       Date:  2007

4.  Reinforcing saccadic amplitude variability.

Authors:  Céline Paeye; Laurent Madelain
Journal:  J Exp Anal Behav       Date:  2011-03       Impact factor: 2.468

5.  Modification of saccadic gain by reinforcement.

Authors:  Laurent Madelain; Céline Paeye; Josh Wallman
Journal:  J Neurophysiol       Date:  2011-04-27       Impact factor: 2.714

6.  Response acquisition and fixed-ratio escalation based on interresponse times in rats.

Authors:  Tracy G Taylor; Chad M Galuska; Kelly Banna; Noushin Yahyavi-Firouz-abadi; Ronald E See
Journal:  J Exp Anal Behav       Date:  2010-03       Impact factor: 2.468

7.  The effects of fixed versus escalating reinforcement schedules on smoking abstinence.

Authors:  Paul Romanowich; R J Lamb
Journal:  J Appl Behav Anal       Date:  2015-01-30
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.