Modeling, learning, and planning together: an application of participatory agent-based modeling to environmental planning

Citation metadata

Authors: Moira L. Zellner, Leilah B. Lyons, Charles J. Hoch, Jennifer Weizeorick, Carl Kunda and Daniel C. Milz
Date: Jan. 2012
From: URISA Journal(Vol. 24, Issue 1)
Publisher: Urban and Regional Information Systems Association (URISA)
Document Type: Report
Length: 11,577 words

Main content

Abstract :

County and regional government agencies use stakeholder committees to ensure representation of diverse interests when planning, but these representatives often are not trained to understand the complexity inherent to human-environmental issues (e.g., groundwater management). Planning professionals use computer models to simulate the interaction effects of different plan-related policies, but most are "black boxes" to stakeholders, who, therefore, are forced to trust the simulations without understanding human-environmental complexity, reducing the opportunities for effective solution building. Agent-based models can represent decisions and environmental dynamics in a rule-based form that invites nonexpert users' involvement in both developing the model and meaningfully interpreting its outputs. We conducted a series of collaborative and developmental agent-based modeling meetings with stakeholders and planners in a rapidly suburbanizing area facing groundwater shortages. Stakeholders learned how to use the models, understand the relationships among the components, interpret the outputs based on these relationships, and suggested modifications with new insights. The enhanced understanding of complex interactions reduced early commitments to policy solutions as stakeholders jointly explored the range of possible outcomes. These results show that agent- based modeling holds promise for use in collaborative planning exercises.

Source Citation

Source Citation
Zellner, Moira L., et al. "Modeling, learning, and planning together: an application of participatory agent-based modeling to environmental planning." URISA Journal, vol. 24, no. 1, Jan. 2012, pp. 77+. Accessed 10 Dec. 2023.

Gale Document Number: GALE|A293544547