Parameter sensitivity analysis is a method used to determine how variations in model parameters affect the outputs of a given system. This technique is crucial for understanding the robustness and reliability of models, especially within adaptive networks and co-evolutionary dynamics, where interactions and feedback loops are prevalent. By identifying which parameters have the most significant influence on outcomes, researchers can better comprehend the behavior of complex systems and make informed decisions regarding their design and management.
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