Fostering Industrial Symbiosis With Agent-Based Simulation and Participatory Modeling

The sciences of industrial ecology, complex systems, and adaptive management are intimately related, since they deal with flows and dynamic interdependencies between system elements of various kinds. As such, the tool kit of complex systems science could enrich our understanding of how industrial ecosystems might evolve over time. In this article, I illustrate how an important tool of complex systems science-agent-based simulation-can help to identify those potential elements of an industrial ecosystem that could work together to achieve more eco-efficient outcomes. For example, I show how agent-based simulation can generate cost-efficient energy futures in which groups of firms behave more eco-efficiently by introducing strategically located clusters of renewable, low-emissions, distributed generation. I then explain how role-playing games and participatory modeling can build trust and reduce conflict about the sharing of common-pool resources such as water and energy among small clusters of evolving agents. Collective learning can encourage potential industrial partners to gradually cooperate by exchanging by-products and/or sharing common infrastructure by dint of their close proximity. This kind of coevolutionary learning, aided by participatory modeling, could help to bring about industrial symbiosis.