An Assessment of Agent-Based Modelling Tools for Community-Based Adaptation to Climate Change
Year: 2024
Type: article
Abstract: Human induced climate change led to the recognition of Community-Based Adaptation (CBA) as one of the remedies in building adaptive capacity and resilience of communities. It recognizes the agency of communities in shaping the optimal strategy. CBA interventions are vital in addressing community needs and contextual specificities, enable participatory and inclusive engagement and thereby facilitate more profound adaptation impacts. Agent-based modelling (ABM) has the potential to be an invaluable approach in developing tailored adaptation strategies considering capacities, resources, skills, priorities, needs and the cultural context of local communities. ABM allows to capture the complex relationships among various components within community decision making on CBA actions, the CBA actions themselves and the environment, however available tools provide for various degrees of freedom in agent definition, sensitivity analysis, scalability, experiment design and output analysis to name a few. This article assesses all available ABM modelling and simulation tools for its application in the context of CBA. NetLogo emerges as the most suitable tool for incorporating and handling the special features of CBA. It is closely followed by GAMA and Envision. The article provides insights and guidance to researchers and practitioners in selecting ABM tools aligned with the specific requirements of their CBA simulations and projects.
Source: Applied Sciences
DOI: 10.3390/app142311264
Authors: Tom Selje, Rayhan Islam, Boris Heinz
Institutions: Technische Universität Berlin, Hudara gGmbH
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,728
OpenAlex ID: W4404971444