Association for Behavior Analysis International

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33rd Annual Convention; San Diego, CA; 2007

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Symposium #273
International Symposium - Feedback Functions and Behavior
Sunday, May 27, 2007
4:00 PM–5:20 PM
Randle A
Area: EAB; Domain: Basic Research
Chair: Michael C. Davison (University of Auckland)
Discussant: M. Jackson Marr (Georgia Institute of Technology)
Abstract: Feedback functions have been used, and will increasingly be used, to answer theoretical questions about behavior. This symposium will introduce the notion of feedback functions (McDowell), present some new data on the effects of feedback between choice and reinforcer ratio (Davison), and present an interpretation of these data for behavior theory (Baum). Marr will then discuss the presentations and provide pointers for the future.
 
A New Candidate Feedback Function for Variable-Interval Schedules.
JACK J. MCDOWELL (Emory University)
Abstract: Feedback functions describe how behavior affects properties of the environment that in turn affect behavior. Organism equations describe how those properties of the environment affect behavior. Feedback functions and organism equations together constitute a complete mathematical account of behavior-environment relationships. Surprisingly, the feedback function for a simple variable-interval (VI) schedule remains a matter of controversy. At least three candidate feedback functions have been proposed. Computational experiments show that feedback on a VI schedule is affected by an organism’s pattern of responding to such an extent that even different types of burst and pause responding generate different feedback relationships. None of the existing candidate functions can describe all of these feedback relationships. However, the sum of a 2-parameter hyperbola and a line with negative slope and zero intercept can describe all of the relationships that have been studied so far, including feedback generated by different types of burst and pause responding. If this equation is the long sought general VI feedback function, then it can be used with confidence in the development of mathematical theories of behavior.
 
Effects of Negative Feedback Functions between Response Ratios and Reinforcer Ratios.
MICHAEL C. DAVISON (University of Auckland), Douglas Elliffe (University of Auckland)
Abstract: Five pigeons were trained on concurrent variable-interval schedules in which the probability of food on one alternative was negatively correlated with the probability of responding on that alternative over the last 3 inter-food intervals - a negative feedback function between log food ratio and log response ratio with a slope of -1. The concurrent VI VI schedules were kept constant and equal while the intercept of the negative feedback function was varied across conditions. Varying the intercept biased the obtained log food ratios, and generalized matching between log response and food ratios resulted. There was no evidence of any relation between the log response ratio in an inter-food interval and log response ratios over the 3 prior inter-food intervals, hence no evidence of any local control of choice. Thus, there was extended control of choice without local control.
 
Local and Extended Control and Analysis.
WILLIAM M. BAUM (University of California, Davis)
Abstract: A molar approach to understanding behavior encourages analysis of data at multiple time scales. At relatively short time scales, analysis is relatively local; at relatively long time scales, analysis is relatively extended. Analysis at any given scale may discover order or may fail to discover order. When we find order at a given scale, we characterize it as control (by environmental events) at that time scale. When we find control at a relatively local level, we usually expect to find additional control at more extended levels of analysis. Thus, analysis at various time scales may reveal control only at relatively extended levels and not necessarily at more local levels.
 

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