{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T20:35:27Z","timestamp":1764794127036,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":6,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,11,5]],"date-time":"2019-11-05T00:00:00Z","timestamp":1572912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,11,5]]},"DOI":"10.1145\/3356470.3365529","type":"proceedings-article","created":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T12:18:47Z","timestamp":1572610727000},"page":"24-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Firm-level behavior control after large-scale urban flooding using multi-agent deep reinforcement learning"],"prefix":"10.1145","author":[{"given":"Shaofeng","family":"Yang","sequence":"first","affiliation":[{"name":"The University of Tokyo, Tokyo, Japan"}]},{"given":"Yoshiki","family":"Ogawa","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Tokyo, Japan"}]},{"given":"Koji","family":"Ikeuchi","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Tokyo, Japan"}]},{"given":"Yuki","family":"Akiyama","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Tokyo, Japan"}]},{"given":"Ryosuke","family":"Shibasaki","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Tokyo, Japan"}]}],"member":"320","published-online":{"date-parts":[[2019,11,5]]},"reference":[{"issue":"1","key":"e_1_3_2_1_1_1","first-page":"12","article-title":"Optimal Risk Mitigation Planning for Supply Chain Disruption","volume":"66","author":"Ohmori S.","year":"2015","unstructured":"S. Ohmori , K. Yoshimoto ( 2015 ). Optimal Risk Mitigation Planning for Supply Chain Disruption , Journal of Japan Industrial Management Association , 66 ( 1 ), 12 -- 22 . S. Ohmori, K. Yoshimoto (2015). Optimal Risk Mitigation Planning for Supply Chain Disruption, Journal of Japan Industrial Management Association, 66(1), 12--22.","journal-title":"Journal of Japan Industrial Management Association"},{"key":"e_1_3_2_1_2_1","volume-title":"Questionnaire survey on disaster prevention measures","author":"Research Ltd Tokyo Shoko","year":"2018","unstructured":"Tokyo Shoko Research Ltd ( 2018 ). Questionnaire survey on disaster prevention measures , http:\/\/www.tokyo-cci.or.jp\/page.jsp?id=1000399, accessed April 5, 2019. Tokyo Shoko Research Ltd (2018). Questionnaire survey on disaster prevention measures, http:\/\/www.tokyo-cci.or.jp\/page.jsp?id=1000399, accessed April 5, 2019."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.20965\/jdr.2019.p0508"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2011.02.008"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.2208\/jscejhe.67.133"},{"key":"e_1_3_2_1_6_1","volume-title":"Learning to communicate with deep multi-agent reinforcement learning. CoRR, abs\/1605.06676","author":"Foerster J. N.","year":"2016","unstructured":"J. N. Foerster , Y. M. Assael , N. de Freitas , and S. Whiteson ( 2016 ). Learning to communicate with deep multi-agent reinforcement learning. CoRR, abs\/1605.06676 . J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson (2016). Learning to communicate with deep multi-agent reinforcement learning. CoRR, abs\/1605.06676."}],"event":{"name":"SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"],"location":"Chicago Illinois","acronym":"SIGSPATIAL '19"},"container-title":["Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3356470.3365529","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3356470.3365529","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:22:54Z","timestamp":1750202574000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3356470.3365529"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,5]]},"references-count":6,"alternative-id":["10.1145\/3356470.3365529","10.1145\/3356470"],"URL":"https:\/\/doi.org\/10.1145\/3356470.3365529","relation":{},"subject":[],"published":{"date-parts":[[2019,11,5]]},"assertion":[{"value":"2019-11-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}