FORUM Fostering Industrial Symbiosis With Agent-Based Simulation and Participatory Modeling

coevolutionary learning companion modeling complex systems science complexity eco-efficiency industrial ecology (IE) Summary The sciences of industrial ecology, complex systems, and adap-tive management are intimately related, since they deal with flows and dynamic interdependencies between system ele-ments of various kinds. As such, the tool kit of complex sys-tems 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 ele-ments 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 en-ergy futures in which groups of firms behave more eco-efficiently by introducing strategically located clusters of re-newable, 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. Address correspondence to