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| Implementing Punishment in an Evolutionary Theory of Behavior Dynamics |
| Friday, September 2, 2022 |
| 10:30 AM–10:55 AM |
| Meeting Level 2; Wicklow Hall 2A |
| Area: PCH |
| Chair: Jack J McDowell (Emory University) |
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| Implementing Punishment in an
Evolutionary Theory of Behavior Dynamics |
| Domain: Theory |
| JACK J MCDOWELL (Emory University) |
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| Abstract: A comprehensive theory of adaptive behavior is a desirable goal for a science of behavior. The evolutionary theory of behavior dynamics is one candidate for such a theory. It 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. This presentation explains how punishment may be implemented in the theory. A key feature of this implementation is that when punishment is superimposed on reinforced responding, the suppressive effect of punishment depends on the amount of reinforcement generated by the target response. The suppressive effect is greater when less reinforcement is generated by the target response than when more is generated. This is a form of reinforcement loss aversion, or “fear of missing out,” as it is sometimes referred to colloquially. Relevant empirical evidence from experiments with live organisms is reviewed, including data from studies that superimpose punishment on concurrent and single alternative schedules. Findings from these studies support this implementation of punishment in the evolutionary theory. |
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