Abstract
This article reports on an agent-based simulation of public participation in decision making about sustainability management. Agents were modeled as socially intelligent actors who communicate using a system of symbols. The goal of the simulation was for agents to reach consensus about which situations in their regional environment to change and which ones not to change as part of a geodesign process for improving water quality in the greater Puget Sound region. As opposed to studying self-organizing behavior at the scale of a local 'commons', our interest was in how online technology supports the self-organizing behavior of agents distributed over a wide regional area, like a watershed or river basin. Geographically-distributed agents interacted through an online platform similar to that used in online field experiments with actual human subjects. We used a factorial research design to vary three interdependent factors each with three different levels. The three factors included 1) the social and geographic distribution of agents (local, regional, international levels), 2) abundance of agents (low, medium, high levels), and 3) diversity of preconceptions (blank slate, clone, social actor levels). We expected that increasing the social and geographic distribution of agents and the diversity of their preconceptions would have a significant impact on agent consensus about which situations to change and which ones not to change. However, our expectations were not met by our findings, which we trace all the way back to our conceptual model and a theoretical gap in sustainability science. The theory of self-organizing resource users does not specify how a group of social actors' preconceptions about a situation is interdependent with their social and geographic orientation to that situation. We discuss the results of the experiment and conclude with prospects for research on the social and geographic dimensions of self-organizing behavior in social-ecological systems spanning wide regional areas.
Highlights
This article reports on an agent-based simulation of public participation in decision making about sustainability management
Based on the theory of self-organizing behavior in sustainability science, we took four subsystem variables of interest including size of the resource system, the number of users, the amount of knowledge sharing among different resource user's mental models, and the level of importance of the resource to each user and developed three simple sets of agent-based properties: Social & Geographic Properties: Agents have a certain social and geographic orientation to situations in their environment Conceptual Properties: Agents carry preconceptions organized into mental models, which they use to reason about situations in their environment Symbolic Properties: Agents are socially intelligent and can communicate their preconceptions to one another using a system of symbols
We were unable to run any treatments at the "high" level of abundance of agents involving roughly 1000 agents because the complexity of the simulation outstripped the power of our desktop computing capabilities
Summary
This article reports on an agent-based simulation of public participation in decision making about sustainability management. Based on the theory of self-organizing behavior in sustainability science, we took four subsystem variables of interest including size of the resource system, the number of users, the amount of knowledge sharing among different resource user's mental models, and the level of importance of the resource to each user and developed three simple sets of agent-based properties: Social & Geographic Properties: Agents have a certain social and geographic orientation to situations in their environment Conceptual Properties: Agents carry preconceptions organized into mental models, which they use to reason about situations in their environment Symbolic Properties: Agents are socially intelligent and can communicate their preconceptions to one another using a system of symbols
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