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How can the impacts of interventions on complex systems be simulated quickly and accurately?

Related Existing Resources

Experimental Practice

Simulator (by Delib)

An online platform engaging citizens in deliberative decision-making by adjusting sliders to reflect priorities and observing consequences of different trade-offs. Used by over 100 organizations worldwide for budget allocation, climate response planning, policing priorities, transport planning, a...
Product

Forio Public Policy simulator

Forio’s public policy simulation solutions enable decision-makers to design policies, analyze outcomes across different scenarios, and build stakeholder consensus. The product helps organizations move beyond static spreadsheet analysis by allowing interactive exploration of how multiple policy in...
Experimental Practice

Beamm.Brussels

Policy impact simulation tool for the Brussels Capital Region
Product

PolicySynth

An open-source TypeScript library combining collective intelligence with AI to improve decision-making in governments and companies through multi-scale AI agent logic flows. Deploys specialized agents (Engineer, Insight, Evaluation) rather than single AI systems, analyzing complex problems, break...
Experimental Practice

FiveThirtyNine LLM forecasting

An AI forecasting system built on GPT-4o generating probability predictions for complex geopolitical and political events through multi-step reasoning: searching for news, compiling facts, weighing arguments, and producing calibrated probabilities. Testing against 177 historical events showed 87....
Research

The Time Machine: Future Scenario Generation Through Generative AI Toolson with Generative AI

Future scenario generation with Generative AI
Research

Empowering Scenario Planning with Artificial Intelligence: A Perspective on Building Smart and Resilient Cities

City-level scenario development (Hao et al. 2024)
Research

Gen

Gen is an open-source framework for probabilistic modeling and inference that automates complex probabilistic inference by providing building blocks for customized algorithms. The framework supports hybrid approaches combining neural networks, variational inference, sequential Monte Carlo, and MC...
Infrastructure

Policy Priority Reference

Policy Priority Inference (PPI) is a research programme and open-source toolkit that models the causal link between government expenditure and policy outcomes using agent-based modeling (a transparent AI approach). It helps governments measure public spending impact on development outcomes and su...