Finding successful strategies in a complex urban sustainability game
Finding successful strategies in a complex urban sustainability game
By Bernardo Monechi, Enrico Ubaldi, PietroGravino, Ilan Chabay & Vittorio Loreto
Abstract
"The adverse effects of unsustainable behaviors on human society are leading to an increasingly urgent and critical need to change policies and practices worldwide. This requires that citizens become informed and engaged in participatory governance and measures leading to sustainable futures. Citizens’ understanding of the inherent complexity of sustainable systems is a necessary (though generally not sufficient) ingredient for them to understand controversial public policies and maintain the core principles of democratic societies. In this work, we present a novel, open-ended experiment where individuals had the opportunity to solve model urban sustainability problems in a purposeful game. Participants were challenged to interact with familiar LEGO blocks representing elements in a complex generative urban economic indicators model. Players seeks to find a specific urban configuration satisfying particular sustainability requirements. We show that, despite the intrinsic complexity and non-linearity of the problems, participants’ ability to make counter-intuitive actions helps them find suitable solutions. Moreover, we show that through successive iterations of the experiment, participants can overcome the difficulties linked to non-linearity and increase the probability of finding the correct solution to the problem. We contend that this kind of what-if platforms could have a crucial role in future approaches to sustainable developments goals.”
Reference
Monechi, B., Ubaldi, E., Gravino, P., Chabay, I., & Loreto, V. (2021, August 03). Finding successful strategies in a complex Urban Sustainability Game. Retrieved December 13, 2021, from https://www.nature.com/articles/s41598-021-95199-w
Keyword
Digital games, sustainability, engagement, strategies, non-linear problems, problem solving, what-if platforms, research