Observations of Society

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Turnover in the Face of Environmental Turbulence

An obvious weakness of our model is that a steady state is always reached at some point, beyond which the code will not change. Since we do not observe this type of phenomenon in the real world, we attempt to reformulate the model to reflect the fact that a societal code, no matter how accurate, can become outdated as the world outside the organization changes. To this end, we allow the environment to change randomly. We suppose that each component of reality changes sign in each time period with a certain probability, known as the "mutation rate." In the graph below, we see what happens to the code knowledge with different amounts of turnover.(1)

Clearly, turnover is essential in this scenario. Without turnover, no exploration occurs. The code comes to share the same beliefs as the agents, at which point no further change is possible. The process then becomes a random walk as reality changes randomly forever. The average code knowledge drops to zero.

On the other hand, with some amount of turnover, the code can maintain some moderate amount of knowledge, even under environmental turbulence. Note that turnover slows down the initial rise in code knowledge, but improves the code knowledge for large time scales. As we expect, some exploration is crucial. Even though it has negative short term effects as resources are diverted away from exploitation, in the longer run, a lack of exploration leads to stagnation and sub-optimal knowledge.

1. Each curve is the average of 200 random societies. Code Learning Rate and Socialization Rate are set to 0.5. N = 50, M = 30.

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