AUTHOR=Molina-Perez Edmundo , Esquivel-Flores Oscar A. , Zamora-Maldonado Hilda TITLE=Computational Intelligence for Studying Sustainability Challenges: Tools and Methods for Dealing With Deep Uncertainty and Complexity JOURNAL=Frontiers in Robotics and AI VOLUME=7 YEAR=2020 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2020.00111 DOI=10.3389/frobt.2020.00111 ISSN=2296-9144 ABSTRACT=

The study of sustainability challenges requires the consideration of multiple coupled systems that are often complex and deeply uncertain. As a result, traditional analytical methods offer limited insights with respect to how to best address such challenges. By analyzing the case of global climate change mitigation, this paper shows that the combination of high-performance computing, mathematical modeling, and computational intelligence tools, such as optimization and clustering algorithms, leads to richer analytical insights. The paper concludes by proposing an analytical hierarchy of computational tools that can be applied to other sustainability challenges.