{"type":"ScholarlyArticle","title":"Modeling the Impact of Policy Interventions for Sustainable Development","authors":[{"name":"Sowmith Nandan Rachuri","slug":"sowmith-nandan-rachuri","given":"Sowmith Nandan","family":"Rachuri","affiliation":"International Institute of Information Technology Bangalore , India"},{"name":"Arpitha Malavalli","slug":"arpitha-malavalli","given":"Arpitha","family":"Malavalli","affiliation":"International Institute of Information Technology Bangalore , India"},{"name":"Niharika Sri Parasa","slug":"niharika-sri-parasa","given":"Niharika Sri","family":"Parasa","affiliation":"International Institute of Information Technology Bangalore , India"},{"name":"Pooja Bassin","slug":"pooja-bassin","given":"Pooja","family":"Bassin","affiliation":"International Institute of Information Technology Bangalore , India"},{"name":"Srinath Srinivasa","slug":"srinath-srinivasa","given":"Srinath","family":"Srinivasa","affiliation":"International Institute of Information Technology Bangalore , India"}],"abstract":"There is an increasing demand to design policy interventions to achieve various targets specified by the UN Sustainable Development Goals by 2030. Designing interventions is a complex task given that the system may often respond in unexpected ways to a given intervention. This could be due to interventions towards a given target, affecting other unrelated variables, and/or interventions leading to acute disparities in nearby geographic areas. In order to address such issues, we propose a novel concept called Stress Modeling that analyzes the holistic impact of a policy intervention by taking into account the interactions within a system, after the intervention. The simulation is based on the postulate that complex systems of interacting entities tend to settle down into \"low energy'' configurations by minimizing differentials in capabilities of neighbouring entities. The simulation shows how policy impact percolates through geospatial boundaries over time and can be applied at any granularity. The theory and the corresponding package have been explained along with a case study analyzing a fertilizer policy in the Agro-climatic Zones of the state of Karnataka, India.","doi":"10.24963/ijcai.2023/841","url":"https://ijcai.org/proceedings/2023/841","pdf":"https://ijcai.org/proceedings/2023/0841.pdf","markdown":"https://ijcai.org/proceedings/2023/841.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/841","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Demo Track","track":"Demo Track","number":841,"pages":{"first":7167,"last":7170},"keywords":["Multidisciplinary Topics and Applications: MDA: Computational sustainability","Machine Learning: ML: Explainable/Interpretable machine learning","Multidisciplinary Topics and Applications: MDA: Energy, environment and sustainability","AI Ethics, Trust, Fairness: ETF: AI and law, governance, regulation","Uncertainty in AI: UAI: Bayesian networks"],"videos":[],"references":[{"position":1,"raw":"[Bassin et al., 2022] Pooja Bassin, Niharika Sri Parasa, Sri- nath Srinivasa, and Sridhar Mandyam. 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