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Public Policy and Decision Science: Difference between revisions
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=== Gathering decision-relevant data ===
* [[Data management, cleaning and imputation|'''Data management, cleaning and imputation''']]
* [[Remote sensing|'''Remote sensing''']]
=== Decision science ===
* '''Decision science'''
* [[Multi-criteria decision-making|'''Multi-criteria decision-making''']]
=== Modeling and planning ===
* '''[[Agent-based modeling]]:''' ABMs are used in simulating the actions and interactions of agents in their environment, and ML can help integrate data-driven insights into these models, for example by learning rules or models for agents based on observational data.
* '''Energy system modeling'''
* '''Urban planning:''' With new techniques such as [[surrogate modeling]], ML can help with complex planning tasks.
* '''[[Power System Planning]]:''' Algorithms for planning new low-carbon energy infrastructure are often large and slow. ML can help speed up or provide proxies for these algorithms.
* '''[[Integrated assessment models]]:''' IAMs are large simulations used to explore future societal pathways that are consistent with climate goals, which can be improved with ML.
=== Ex-post policy analysis ===
* '''Causal inference with machine learning'''
== Background Readings ==
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