{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T04:03:39Z","timestamp":1750133019152,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":3,"publisher":"ACM","funder":[{"name":"JSPS, Japan KAKENHI","award":["JP23K24952 and JP24K20901"],"award-info":[{"award-number":["JP23K24952 and JP24K20901"]}]},{"name":"DAIKIN Industries, Ltd."}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,17]]},"DOI":"10.1145\/3679240.3734672","type":"proceedings-article","created":{"date-parts":[[2025,6,16]],"date-time":"2025-06-16T13:13:42Z","timestamp":1750079622000},"page":"973-975","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Deep Reinforcement Learning- and Linear Programming-based Hierarchical Aggregation Framework for Demand-side Flexibility"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-4066-5266","authenticated-orcid":false,"given":"Ren","family":"Sasaki","sequence":"first","affiliation":[{"name":"The University of Osaka, OSAKA, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8107-4260","authenticated-orcid":false,"given":"Zhao","family":"Dafang","sequence":"additional","affiliation":[{"name":"The University of Osaka, OSAKA, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9626-0944","authenticated-orcid":false,"given":"Hiroki","family":"Nishikawa","sequence":"additional","affiliation":[{"name":"The University of Osaka, OSAKA, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7843-5907","authenticated-orcid":false,"given":"Ittetsu","family":"Taniguchi","sequence":"additional","affiliation":[{"name":"The University of Osaka, OSAKA, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1894-2448","authenticated-orcid":false,"given":"Takao","family":"Onoye","sequence":"additional","affiliation":[{"name":"The University of Osaka, OSAKA, Japan"}]}],"member":"320","published-online":{"date-parts":[[2025,6,16]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","unstructured":"Donald Azuatalam Wee-Lih Lee Frits de Nijs and Ariel Liebman. 2020. Reinforcement learning for whole-building HVAC control and demand response. Energy and AI 2 (2020) 100020. 10.1016\/j.egyai.2020.100020","DOI":"10.1016\/j.egyai.2020.100020"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3632775.3661975"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/PESGM41954.2020.9281946"}],"event":{"name":"E-Energy '25: The 16th ACM International Conference on Future and Sustainable Energy Systems","location":"Rotterdam Netherlands","acronym":"E-Energy '25","sponsor":["SIGEnergy ACM Special Interest Group on Energy Systems and Informatics"]},"container-title":["Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3679240.3734672","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,16]],"date-time":"2025-06-16T14:01:37Z","timestamp":1750082497000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3679240.3734672"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,16]]},"references-count":3,"alternative-id":["10.1145\/3679240.3734672","10.1145\/3679240"],"URL":"https:\/\/doi.org\/10.1145\/3679240.3734672","relation":{},"subject":[],"published":{"date-parts":[[2025,6,16]]},"assertion":[{"value":"2025-06-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}