{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:19:37Z","timestamp":1774120777410,"version":"3.50.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1834701"],"award-info":[{"award-number":["CNS-1834701"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1551661"],"award-info":[{"award-number":["CNS-1551661"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["ECCS-1610471"],"award-info":[{"award-number":["ECCS-1610471"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Sustain. Comput."],"published-print":{"date-parts":[[2021,7,1]]},"DOI":"10.1109\/tsusc.2019.2910533","type":"journal-article","created":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T22:30:18Z","timestamp":1558477818000},"page":"370-384","source":"Crossref","is-referenced-by-count":45,"title":["Deep Reinforcement Learning for Joint Datacenter and HVAC Load Control in Distributed Mixed-Use Buildings"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6322-6192","authenticated-orcid":false,"given":"Tianshu","family":"Wei","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9003-4324","authenticated-orcid":false,"given":"Shaolei","family":"Ren","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7700-4099","authenticated-orcid":false,"given":"Qi","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1023\/A:1017928328829"},{"key":"ref38","first-page":"503","article-title":"Tree-based batch mode reinforcement learning","volume":"6","author":"ernst","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2017.2690673"},{"key":"ref32","article-title":"Calculating total cooling requirements for data centers.","author":"neil","year":"0"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2010.5461933"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/2318857.2254779"},{"key":"ref37","author":"alpaydin","year":"2004","journal-title":"Introduction to Machine Learning (Adaptive Computation and Machine Learning)"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992698"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1080\/19401493.2010.518631"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7363769"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3061639.3062224"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IGCC.2016.7892609"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.2014.6858874"},{"key":"ref2","article-title":"Pue: A comprehensive examination of the metric","year":"2012"},{"key":"ref1","article-title":"Buildings energy data book.","year":"0"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CoASE.2015.7294119"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3233\/AIS-140288"},{"key":"ref21","article-title":"A method for computing optimal set-point schedules for HVAC systems","author":"nikovski","year":"2013","journal-title":"Proc REHVA World Congr CLIMA"},{"key":"ref24","article-title":"Transforming cooling optimization for green data center via deep reinforcement learning","volume":"abs 1709 5077","author":"li","year":"2017","journal-title":"CoRR"},{"key":"ref23","article-title":"Experimental analysis of data-driven control for a building heating system","volume":"abs 1507 3638","author":"costanzo","year":"2015","journal-title":"CoRR"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/nature16961"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2903738"},{"key":"ref51","year":"0"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2015.2417566"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/1107499.1107504"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2016.2550454"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.7873\/DATE.2015.0786"},{"key":"ref53","article-title":"Standard 55&#x2013;2004-thermal environmental conditions for human occupancy","year":"2004"},{"key":"ref52","year":"0"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2015.2444845"},{"key":"ref11","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-01741-4","author":"barroso","year":"2013","journal-title":"The Datacenter as a Computer An Introduction to the Design of Warehouse-Scale Machines"},{"key":"ref40","author":"riedmiller","year":"2005","journal-title":"Neural fitted q iteration-first experiences with a data efficient neural reinforcement learning method"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2015.2434797"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1109\/TCST.2011.2124461","article-title":"Model predictive control for the operation of building cooling systems","volume":"20","author":"ma","year":"2012","journal-title":"IEEE Trans Control Syst Technol"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.2010.5530680"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2015.07.050"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1115\/DSCC2011-6078"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2593069.2596670"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2014.7001351"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-23461-8_1"},{"key":"ref4","article-title":"Scaling up energy efficiency across the data center industry: Evaluating key drivers and barriers","year":"2014"},{"key":"ref3","year":"0"},{"key":"ref6","article-title":"Calculating space and power density requirements for data centers","author":"rasmussen","year":"0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2008.09.003"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2013.270"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1080\/19401493.2013.783118"},{"key":"ref49","first-page":"1093","article-title":"A learning agent for heat-pump thermostat control","author":"urieli","year":"2013","journal-title":"Proc Int Conf Auton Agents Multi-Agent Syst"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.08.003"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref45","article-title":"Playing atari with deep reinforcement learning","volume":"abs 1312 5602","author":"mnih","year":"2013","journal-title":"CoRR"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref47","year":"0"},{"key":"ref42","first-page":"696","author":"rumelhart","year":"0","journal-title":"Neurocomputing Foundations of Research"},{"key":"ref41","first-page":"9","author":"lecun","year":"2012","journal-title":"Efficient backprop"},{"key":"ref44","author":"alpaydin","year":"2010","journal-title":"Introduction to Machine Learning"},{"key":"ref43","article-title":"Lecture 6a overview of mini&#x2013;batch gradient descent.","author":"hinton","year":"0"}],"container-title":["IEEE Transactions on Sustainable Computing"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/7274860\/9531050\/8691496-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274860\/9531050\/08691496.pdf?arnumber=8691496","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,16]],"date-time":"2023-09-16T19:59:48Z","timestamp":1694894388000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8691496\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":57,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tsusc.2019.2910533","relation":{},"ISSN":["2377-3782","2377-3790"],"issn-type":[{"value":"2377-3782","type":"electronic"},{"value":"2377-3790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}