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We live in a complex globalized world where large-scale economic, social, technological and ecological systems interact profoundly. Often, systems are inherently complex and uncertain and our knowledge of them is limited, either through ignorance or partial knowledge, or due to conflicting interpretations by different actors in the world. In 2018, UPF launched the Planetary Wellbeing initiative, a project that demonstrates the University’s commitment to the major challenges of the 21st century.
Interactive Policy Explorer for Planetary Wellbeing (IPER) is a new project which started on 21 January at a kick-off meeting on the Poblenou campus at UPF led by the researchers Mario Ceresa and Miguel Ángel González Ballester (ICREA) of the SiMBioSys research group of the BCNMedTech unit at the Department of Information and Communication Technologies (DTIC), UPF, involving the researchers Cathryn Tonne and Josep Maria Antó of ISGlobal.
The goal the IPER project is to create a simulator of various models interconnected via systems modelling tools, specifically agent-based simulations. An initial prototype will focus mainly on pollution, health and transport in the Barcelona metropolitan area.
The project is based on the assumption according to which although experts believe that humans have never been as healthy as they are today, natural ecological systems have deteriorated greatly in recent times. There is growing awareness that human health is profoundly linked to the environment, although it is not clear which are the effects of applying one or another policy on health and the environment, both in terms of human activities and planetary wellbeing.
“Hence the need for good interpretative models of our environment that promote policies and simulate the consequences of decision-making, either to prevent potential risks, to choose between possible responses to emergencies or to improve the general welfare”, Ceresa and González Ballester assert.
IPER is a one-year interdisciplinary project merging high performance computing, artificial intelligence, social sciences, public health and air quality methodologies. To determine the effects of different policies on this complex network of interactions, the project will use massive scale agent simulations with advanced reinforcement learning methods. This will help all stakeholders, academic researchers, policy makers and the private sector, to gain information about the long-term effects of a given policy decision.
