Literature DB >> 22478030

Quantitative prediction and molar description of the environment.

W M Baum.   

Abstract

Molecular explanations of behavior, based on momentary events and variables that can be measured each time an event occurs, can be contrasted with molar explanations, based on aggregates of events and variables that can be measured only over substantial periods of time. Molecular analyses cannot suffice for quantitative accounts of behavior, because the historical variables that determine behavior are inevitably molar. When molecular explanations are attempted, they always depend on hypothetical constructs that stand as surrogates for molar environmental variables. These constructs allow no quantitative predictions when they are vague, and when they are made precise, they become superfluous, because they can be replaced with molar measures. In contrast to molecular accounts of phenomena like higher responding on ratio schedules than interval schedules and free-operant avoidance, molar accounts tend to be simple and straightforward. Molar theory incorporates the notion that behavior produces consequences that in turn affect the behavior, the notion that behavior and environment together constitute a feedback system. A feedback function specifies the dependence of consequences on behavior, thereby describing properties of the environment. Feedback functions can be derived for simple schedules, complex schedules, and natural resources. A complete theory of behavior requires describing the environment's feedback functions and the organism's functional relations. Molar thinking, both in the laboratory and in the field, can allow quantitative prediction, the mark of a mature science.

Year:  1989        PMID: 22478030      PMCID: PMC2742112          DOI: 10.1007/bf03392493

Source DB:  PubMed          Journal:  Behav Anal        ISSN: 0738-6729


  7 in total

1.  The role of temporal discriminations in the reinforcement of Sidman avoidance behavior.

Authors:  D ANGER
Journal:  J Exp Anal Behav       Date:  1963-07       Impact factor: 2.468

2.  Traumatic avoidance learning: the principles of anxiety conservation and partial irreversibility.

Authors:  R L SOLOMON; L C WYNNE
Journal:  Psychol Rev       Date:  1954-11       Impact factor: 8.934

3.  Optimization and the matching law as accounts of instrumental behavior.

Authors:  W M Baum
Journal:  J Exp Anal Behav       Date:  1981-11       Impact factor: 2.468

4.  The correlation-based law of effect.

Authors:  W M Baum
Journal:  J Exp Anal Behav       Date:  1973-07       Impact factor: 2.468

5.  Method and theory in the study of avoidance.

Authors:  R J Herrnstein
Journal:  Psychol Rev       Date:  1969-01       Impact factor: 8.934

6.  On the measurement of reinforcement frequency in the study of preference.

Authors:  P Killeen
Journal:  J Exp Anal Behav       Date:  1968-05       Impact factor: 2.468

7.  Negative reinforcement as shock-frequency reduction.

Authors:  R J Herrnstein; P N Hineline
Journal:  J Exp Anal Behav       Date:  1966-07       Impact factor: 2.468

  7 in total
  8 in total

1.  Rethinking reinforcement: allocation, induction, and contingency.

Authors:  William M Baum
Journal:  J Exp Anal Behav       Date:  2012-01       Impact factor: 2.468

2.  Functions of the environment in behavioral evolution.

Authors:  S S Glenn; D P Field
Journal:  Behav Anal       Date:  1994

3.  Contingency and behavior analysis.

Authors:  K A Lattal
Journal:  Behav Anal       Date:  1995

4.  Molar functional relations and clinical behavior analysis: implications for assessment and treatment.

Authors:  Thomas J Waltz; William C Follette
Journal:  Behav Anal       Date:  2009

5.  Infants' feats of inference: A commentary on Bower and Watson.

Authors:  J Marr
Journal:  Behav Anal       Date:  1997

6.  Dynamics of choice: a tutorial.

Authors:  William M Baum
Journal:  J Exp Anal Behav       Date:  2010-09       Impact factor: 2.468

7.  The effects of a local negative feedback function between choice and relative reinforcer rate.

Authors:  Michael Davison; Douglas Elliffe; M Jackson Marr
Journal:  J Exp Anal Behav       Date:  2010-09       Impact factor: 2.468

8.  Large-N Rat Data Enables Phenotyping of Risky Decision-Making: A Retrospective Analysis of Brain Injury on the Rodent Gambling Task.

Authors:  Cole Vonder Haar; Michelle A Frankot; A Matthew Reck; Virginia Milleson; Kris M Martens
Journal:  Front Behav Neurosci       Date:  2022-04-25       Impact factor: 3.617

  8 in total

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