Paper

Computational Modeling of Human Adaptation in Urban Infrastructure Management under Extreme Conditions: A Case Study of Subway Flood Scenarios

arXiv:2606.06429v1 Announce Type: new Abstract: Decision-making in urban infrastructure management during extreme events relies heavily on human operators, yet current computational support systems often fail to account for non-monotonic human adaptation and latent psychological biases like overconfidence and defensive overcorrection. This study addresses this gap by integrating Instance-Based Learning Theory (IBLT) into the domain of civil engineering computing. We establish a computational cognitive architecture that simulates operator decision processes through the mathematical mechanisms…

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