Using Reinforcement Learning to Integrate Subjective Wellbeing into Climate Adaptation Decision Making

Vandervoort, Arthur; Costa, Miguel; Petersen, Morten W.; Drews, Martin; Haustein, Sonja; Morrissey, Karyn; Pereira, Francisco C.

Using Reinforcement Learning to Integrate Subjective Wellbeing into Climate Adaptation Decision Making (Proposals Track)

Arthur Vandervoort (Technical University of Denmark); Miguel Costa (Technical University of Denmark); Morten W. Petersen (Technical University of Denmark); Martin Drews (Technical University of Denmark); Sonja Haustein (Technical University of Denmark); Karyn Morrissey (University of Galway); Francisco C. Pereira (Technical University of Denmark)

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Societal Adaptation & Resilience Behavioral and Social Science Cities & Urban Planning Climate Science & Modeling Disaster Management and Relief Extreme Weather Health Transportation Reinforcement Learning

Abstract

Subjective wellbeing is a fundamental aspect of human life, influencing life expectancy and economic productivity, among others. Mobility plays a critical role in maintaining wellbeing, yet the increasing frequency and intensity of both nuisance and high-impact floods due to climate change are expected to significantly disrupt access to activities and destinations, thereby affecting overall wellbeing. Addressing climate adaptation presents a complex challenge for policymakers, who must select and implement policies from a broad set of options with varying effects while managing resource constraints and uncertain climate projections. In this work, we propose a multi-modular framework that uses reinforcement learning as a decision-support tool for climate adaptation in Copenhagen, Denmark. Our framework integrates four interconnected components: long-term rainfall projections, flood modeling, transport accessibility, and wellbeing modeling. This approach enables decision-makers to identify spatial and temporal policy interventions that help sustain or enhance subjective wellbeing over time. By modeling climate adaptation as an open-ended system, our framework provides a structured framework for exploring and evaluating adaptation policy pathways. In doing so, it supports policymakers to make informed decisions that maximize wellbeing in the long run.