{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T07:50:40Z","timestamp":1772005840991,"version":"3.50.1"},"reference-count":25,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1728165"],"award-info":[{"award-number":["1728165"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3008083","type":"journal-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T20:19:22Z","timestamp":1594239562000},"page":"124894-124904","source":"Crossref","is-referenced-by-count":4,"title":["Modeling the System Acquisition Using Deep Reinforcement Learning"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1902-3232","authenticated-orcid":false,"given":"Salar","family":"Safarkhani","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5266-105X","authenticated-orcid":false,"given":"Ilias","family":"Bilionis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4873-3089","authenticated-orcid":false,"given":"Jitesh H.","family":"Panchal","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"mnih","year":"2015","journal-title":"Nature"},{"key":"ref11","first-page":"2094","article-title":"Deep reinforcement learning with double q-learning","author":"van hasselt","year":"2016","journal-title":"Proc 13th AAAI Conf Artif Intell"},{"key":"ref12","article-title":"Dueling network architectures for deep reinforcement learning","author":"wang","year":"2015","journal-title":"arXiv 1511 06581"},{"key":"ref13","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","author":"mnih","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref14","article-title":"Continuous control with deep reinforcement learning","author":"lillicrap","year":"2015","journal-title":"arXiv 1509 02971"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1038\/nature24270"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1007\/978-3-319-71682-4_5","article-title":"Cooperative multi-agent control using deep reinforcement learning","author":"gupta","year":"2017","journal-title":"Proc 1st Int Conf Autonomous Agents Multiagent Syst"},{"key":"ref17","first-page":"6379","article-title":"Multi-agent actor-critic for mixed cooperative-competitive environments","author":"lowe","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","first-page":"1547","article-title":"Microscopic traffic simulation by cooperative multi-agent deep reinforcement learning","author":"bacchiani","year":"2019","journal-title":"Proc 8th Int Conf Auton Agents Multiagent Syst"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272021"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2020.2964668"},{"key":"ref3","author":"walden","year":"2015","journal-title":"Systems Engineering Handbook A guide for System Life Cycle Processes and Activities"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-5974-3_28"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1115\/1.4029150"},{"key":"ref8","year":"2018","journal-title":"Office of the Under Secretary of Defense for Acquisition and Sustainment"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1115\/DETC2018-85941"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/11494676_2"},{"key":"ref9","author":"sutton","year":"2018","journal-title":"Reinforcement Learning An Introduction"},{"key":"ref1","year":"2019","journal-title":"Assessments of Major Projects"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3315772"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3372823"},{"key":"ref21","article-title":"Deep reinforcement learning for cyber security","author":"thi nguyen","year":"2019","journal-title":"arXiv 1906 05799"},{"key":"ref24","article-title":"A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning","author":"brochu","year":"2010","journal-title":"ArXiv 1012 2599"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1115\/1.4040548"},{"key":"ref25","first-page":"663","article-title":"Algorithms for inverse reinforcement learning","author":"ng","year":"2000","journal-title":"Proc 17th Int Conf Mach Learn"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6287639\/8948470\/9136669-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09136669.pdf?arnumber=9136669","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T18:53:36Z","timestamp":1649444016000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9136669\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3008083","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}