McDowell’s evolutionary theory of behavior dynamics (McDowell, 2004) instantiates populations of behaviors (abstractly represented by integers) that evolve under the selection pressure of the environment in the form of positive reinforcement. Each generation gives rise to the next via low‐level Darwinian processes of selection, recombination, and mutation. The emergent patterns can be analyzed and compared to those produced by biological organisms. The purpose of this project was to explore the effects of high mutation rates on behavioral variability in environments that arranged different reinforcer rates and magnitudes. Behavioral variability increased with the rate of mutation. High reinforcer rates and magnitudes reduced these effects; low reinforcer rates and magnitudes augmented them. These results are in agreement with live‐organism research on behavioral variability. Various combinations of mutation rates, reinforcer rates, and reinforcer magnitudes produced similar high‐level outcomes (equifinality). These findings suggest that the independent variables that describe an experimental condition interact; that is, they do not influence behavior independently. These conclusions have implications for the interpretation of high levels of variability, mathematical undermatching, and the matching theory. The last part of the discussion centers on a potential biological counterpart for the rate of mutation, namely spontaneous fluctuations in the brain's default mode network.