Integrated System Modeling (MODEL)
Collective Learning for a Sustainable Future
We reshape human-environment modeling to identify critical leverage points for sustainability transitions. The dynamics of collective action at scale – in which large collectives of intelligent actors in complex environments seek ways to improve their joint well-being – are critical for a sustainable future, yet unresolved. The fundamental question is: Are we, as the human species, intelligent enough to maintain our life-support system and organize a good life for all? To move forward with this challenge, we develop formal models of collective learning.
We are sustainability system scientists. No single academic discipline alone is up to the task. We are a young, strongly evolving, interdisciplinary team building bridges between Complex System Science, Cognitive Science (especially Multi-Agent Reinforcement Learning), Social-Ecological Resilience, and Sustainability Economics. To merge all of these perspectives, we practice humility in collective learning.
We focus on excellence in developing theory-driven computational models. They bridge mathematical with computational modeling to eventually reshape our mental and verbal models of Nature-Society relationships. We openly talk about our models and their assumptions. We make them fully transparent, open source, and reproducible. We also educate the next generation of sustainability system modelers. Why? To initiate large-scale collective learning for a sustainable future.
