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An evolutionary theory of behavior dynamics applied to concurrent ratio schedules
1Department of Psychology, Emory University, Atlanta, USA.
Journal of the Experimental Analysis of Behavior
|September 9, 2018
Summary
Artificial organisms evolved using Darwinian principles showed adaptive behavior dynamics. They favored options with better outcomes on concurrent ratio schedules, supporting evolutionary theory.
Area of Science:
- Behavioral science
- Artificial intelligence
- Evolutionary computation
Background:
- Adaptive behavior dynamics are crucial for survival.
- Evolutionary principles can model complex behaviors.
- Concurrent ratio schedules are standard behavioral paradigms.
Purpose of the Study:
- To test an evolutionary theory of adaptive behavior dynamics.
- To simulate behavior using artificial organisms (AOs) on concurrent ratio schedules.
- To evaluate the theory's consistency with empirical findings.
Main Methods:
- Developed a genetic algorithm implementing Darwinian selection, reproduction, and mutation.
- Animated AOs with the evolutionary theory.
- Observed AO behavior on concurrent ratio schedules with unequal and equal ratios.
Main Results:
- AOs exclusively chose the component with the smaller ratio when ratios were unequal (within certain limits).
- AOs exclusively chose one component when ratios were equal (within certain limits).
- AO preference adjusted rapidly to ratio changes and was a continuous function of ratio value.
Conclusions:
- The simulated adaptive behavior dynamics align with empirical observations of live organisms.
- The results support the tested evolutionary theory of behavior.
- The genetic algorithm effectively models evolutionary adaptive behavior.
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