Presenting at NeurIPS 2025: adaptive agents for climate risk

Accepted at NeurIPS 2025: We will be presenting Adaptive Learning in Spatial Agent-Based Models for Climate Risk Assessment: A Geospatial Framework with Evolutionary Economic Agents at the Tackling Climate Change with Machine Learning workshop to present how a complexity-science driven approach to climate risk modelling — with a spatial network of economic agents that learn and adapt to increasing climate risks — can provide a better approach for climate risk quantification and management.

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. Adaptive learning behaviours 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.

Read full paper here: https://arxiv.org/pdf/2509.18633