{"type":"ScholarlyArticle","title":"Non-Parametric Stochastic Sequential Assignment With Random Arrival Times","authors":[{"name":"Danial Dervovic","slug":"danial-dervovic","given":"Danial","family":"Dervovic","affiliation":""},{"name":"Parisa Hassanzadeh","slug":"parisa-hassanzadeh","given":"Parisa","family":"Hassanzadeh","affiliation":""},{"name":"Samuel Assefa","slug":"samuel-assefa","given":"Samuel","family":"Assefa","affiliation":""},{"name":"Prashant Reddy","slug":"prashant-reddy","given":"Prashant","family":"Reddy","affiliation":""}],"abstract":"We consider a problem wherein jobs arrive at random times and assume random values. Upon each job arrival, the decision-maker must decide immediately whether or not to accept the job and gain the value on offer as a reward, with the constraint that they may only accept at most n jobs over some reference time period. The decision-maker only has access to M independent realisations of the job arrival process. We propose an algorithm, Non-Parametric Sequential Allocation (NPSA), for solving this problem. Moreover, we prove that the expected reward returned by the NPSA algorithm converges in probability to optimality as M grows large. We demonstrate the effectiveness of the algorithm empirically on synthetic data and on public fraud-detection datasets, from where the motivation for this work is derived.","doi":"10.24963/ijcai.2021/579","url":"https://ijcai.org/proceedings/2021/579","pdf":"https://ijcai.org/proceedings/2021/0579.pdf","markdown":"https://ijcai.org/proceedings/2021/579.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/579","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Uncertainty in AI","track":"Main Track","number":579,"pages":{"first":4214,"last":4220},"keywords":["Uncertainty in AI: Sequential Decision Making","Planning and Scheduling: Planning and Scheduling","Machine Learning: Cost-Sensitive Learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}