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Overlapping Versus Non-overlapping Generations

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Markov Chain Aggregation for Agent-Based Models

Part of the book series: Understanding Complex Systems ((UCS))

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Abstract

In this chapter, we inspect well-known population genetics and social dynamics models. In these models, interacting individuals, while participating in a self-organizing process, give rise to the emergence of complex behaviors and patterns. While one main focus in population genetics is on the adaptive behavior of a population, social dynamics is more often concerned with the splitting of a connected array of individuals into a state of global polarization, that is, the emergence of speciation. Using numerical simulations and the mathematical tools developed in the previous chapters we show that the way the mechanisms of selection, interaction and replacement are constrained and combined in the modeling have an important bearing on both adaptation and the emergence of speciation. Differently (un)constraining the mechanism of individual replacement provides the conditions required for either speciation or adaptation, since these features appear as two opposing phenomena, not achieved by one and the same model. Even though natural selection, operating as an external, environmental mechanism, is neither necessary nor sufficient for the creation of speciation, our modeling exercises highlight the important role played by natural selection in the interplay of the evolutionary and the self-organization modeling methodologies.

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Notes

  1. 1.

    See Castellano et al. (2009) for a comprehensive overview over models in this field.

  2. 2.

    Notice that the agent choice is with replacement so that an individual may be chosen twice. This corresponds to self-fertilization and we allow it to keep the model as simple as possible.

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Banisch, S. (2016). Overlapping Versus Non-overlapping Generations. In: Markov Chain Aggregation for Agent-Based Models. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-24877-6_8

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