Global Systems Science is a FET Proactive initiative under Horizon 2020 that seeks to improve the way scientific knowledge can help inform and evaluate policy and societal responses to global challenges like climate change and global financial crises. The making of policies coping with such global systems is a process that necessarily involves the participation of stakeholders with very diverse backgrounds (political, legal, social, economic, technical, ecologic, etc.), each of them with their own interests, expectations, constraints, targets and objectives. People play a central role in this kind of collective decision making and generally the quest for solutions to a problem intertwines its very understanding and specification.
To some extent, traditional “what-if” style computer simulations can assist in this process provided they employ the right narratives and adequate high-level, qualitative models to separate the policy question from the underlying scientific details. Domain-specific Languages (DSL) embedded in Functional Programming (FP) languages like Haskell offer a promising way to implement scalable and verifiable simulators. But the traditional use of simulators is essentially an iterative trial-and-error process, way too tedious for “on-line” execution in a moderated group session: possible policy measures have to be imagined and tried, their simulated effects contrasted with the desired objectives and targets, and this process has to be repeated many times until results are considered good enough for everyone. A paradigm shift is needed towards rapid assessment tools that are real problem solvers in which targets and stakeholders’ objectives can be taken along as input from the very beginning and the required actions and measures to be implemented are the solutions produced. Constraint Programming (CP) has already demonstrated to enable a similar paradigm shift e.g. in the case of managed physical systems like water and power distribution networks.
The GRACeFUL project pursues laying a base for domain-specific languages aimed at building scalable rapid assessment tools for collective policy making in global systems. It involves several different disciplines. At the top policy-modelling level, we adopt and adapt the socially-inspired discipline of Group Model Building, well-known from system dynamics. This process is formalized through a dedicated embedded DSL and backed by visual forms of conceptual modelling and flavoured with gamification aspects and visual analytics. At the host-language level, we work on combining the declarative paradigms of CP and FP. In the latter context, specific work is being done on domain-specific constraints, constraint composition, and composable solvers and heuristics.
Results are applied and validated for a specific problem case of Climate-Resilient Urban Design in the city of Dordrecht in The Netherlands, but the ambition is providing a general framework and approach applicable to several other Global Systems.