{"type":"ScholarlyArticle","title":"Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management","authors":[{"name":"Amrita Gupta","slug":"amrita-gupta","given":"Amrita","family":"Gupta","affiliation":"School of Computational Science & Engineering , Georgia Institute of Technology"},{"name":"Mehrdad Farajtabar","slug":"mehrdad-farajtabar","given":"Mehrdad","family":"Farajtabar","affiliation":"School of Computational Science & Engineering , Georgia Institute of Technology"},{"name":"Bistra Dilkina","slug":"bistra-dilkina","given":"Bistra","family":"Dilkina","affiliation":"Department of Computer Science , University of Southern California"},{"name":"Hongyuan Zha","slug":"hongyuan-zha","given":"Hongyuan","family":"Zha","affiliation":"School of Computational Science & Engineering , Georgia Institute of Technology"}],"abstract":"The spread of invasive species to new areas threatens the stability of ecosystems and causes major economic losses. We propose a novel approach to minimize the spread of an invasive species given a limited intervention budget. We first model invasive species spread using Hawkes processes, and then derive closed-form expressions for characterizing the effect of an intervention action on the invasion process. We use this to obtain an optimal intervention plan based on an integer programming formulation, and compare the optimal plan against several ecologically-motivated heuristic strategies used in practice. We present an empirical study of two variants of the invasive control problem: minimizing the final rate of invasions, and minimizing the number of invasions at the end of a given time horizon. The optimized intervention achieves nearly the same level of control that would be attained by completely eradicating the species, but at only 60-80\\% of the cost.","doi":"10.24963/ijcai.2018/470","url":"https://ijcai.org/proceedings/2018/470","pdf":"https://ijcai.org/proceedings/2018/0470.pdf","markdown":"https://ijcai.org/proceedings/2018/470.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/470","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Machine Learning Applications","track":"Main track","number":470,"pages":{"first":3385,"last":3392},"keywords":["Multidisciplinary Topics and Applications: Computational Sustainability","Machine Learning Applications: Networks","Machine Learning: Time-series;Data Streams"],"videos":[],"references":[{"position":1,"raw":"[Arim et al., 2006] Matías Arim, Sebastián Abades, Paula Neill, Mauricio Lima, and Pablo Marquet. 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