Complex adaptive systems (CASs) consist of diverse, locally interacting components that are subject to selection. Examples include learning brains, developing individuals, economies, ecosystems, and the biosphere. In such systems, hierarchical organization, continual novelty and adaptation, and nonequilibrium dynamics are known to emerge. As a result, the behavior of a CAS is characterized by nonlinearity, historical contingency, thresholds, and multiple basins of attraction. A key question in current CAS research has been the relationship between resilience and criticality. Some authors suggest that a CAS will generally evolve toward self-organized criticality. By being maintained near the edge of chaos, such systems might maximize information processing. In this way, criticality might enhance the ability of CASs to adapt to changing environments and efficiently utilize resources, making systems become more resilient over time.
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