Adaptive Learning in Spatial Agent-Based Models for Climate Risk Assessment: A Geospatial Framework with Evolutionary Economic Agents
Yara Mohajerani
TL;DR
Addresses climate risk with spatial heterogeneity and adaptive economic behaviour. It introduces a Mesa-based geospatial ABM integrated with CLIMADA hazard assessment and an evolutionary learning system governing six firm strategies. Using riverine flood projections under $RCP8.5$, results show that adaptation reduces production losses and brings outputs toward baseline by 2100, while indirect supply-chain risks persist and end-of-century prices rise by about 5.6%. The framework provides financial institutions and companies a practical tool to quantify direct and cascading climate risks and to compare cost-effective adaptation strategies, with open-source availability at the referenced repository.
Abstract
Climate risk assessment requires modelling complex interactions between spatially heterogeneous hazards and adaptive economic systems. We present a novel geospatial agent-based model that integrates climate hazard data with evolutionary learning for economic agents. Our framework combines Mesa-based spatial modelling with CLIMADA climate impact assessment, introducing adaptive learning behaviours that allow firms to evolve strategies for budget allocation, pricing, wages, and risk adaptation through fitness-based selection and mutation. We demonstrate the framework using riverine flood projections under RCP8.5 until 2100, showing that evolutionary adaptation enables firms to converge with baseline (no hazard) production levels after decades of disruption due to climate stress. Our results reveal systemic risks where even agents that are not directly exposed to floods face impacts through supply chain disruptions, with the end-of-century average price of goods 5.6% higher under RCP8.5 compared to the baseline in our illustrative economic network. This open-source framework provides financial institutions and companies with tools to quantify both direct and cascading climate risks while evaluating cost-effective adaptation strategies.