乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T05:18:22Z","timestamp":1726031902236},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030217402"},{"type":"electronic","value":"9783030217419"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-21741-9_13","type":"book-chapter","created":{"date-parts":[[2019,6,17]],"date-time":"2019-06-17T23:09:30Z","timestamp":1560812970000},"page":"123-132","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Dynamic Resource Allocation During Natural Disasters Using Multi-agent Environment"],"prefix":"10.1007","author":[{"given":"Alina","family":"Vereshchaka","sequence":"first","affiliation":[]},{"given":"Wen","family":"Dong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,6,5]]},"reference":[{"key":"13_CR1","unstructured":"United Nations Office for Disaster Risk Reduction (UNISDR) and Centre for Research on the Epidemiology of Disasters (CRED), Economic losses, poverty and disasters, pp. 1998\u20132017 (2018)"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Frias-Martinez, E., Williamson, G., Frias-Martinez, V.: An agent-based model of epidemic spread using human mobility and social network information. In: 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing, pp. 57\u201364. IEEE (2011)","DOI":"10.1109\/PASSAT\/SocialCom.2011.142"},{"issue":"6104","key":"13_CR3","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1126\/science.1223467","volume":"338","author":"A Wesolowski","year":"2012","unstructured":"Wesolowski, A., et al.: Quantifying the impact of human mobility on malaria. Science 338(6104), 267\u2013270 (2012)","journal-title":"Science"},{"issue":"8","key":"13_CR4","doi-asserted-by":"publisher","first-page":"e1001083","DOI":"10.1371\/journal.pmed.1001083","volume":"8","author":"L Bengtsson","year":"2011","unstructured":"Bengtsson, L., Lu, X., Thorson, A., Garfield, R., Von Schreeb, J.: Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti. PLoS Med. 8(8), e1001083 (2011)","journal-title":"PLoS Med."},{"key":"13_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1007\/978-3-642-29047-3_34","volume-title":"Social Computing, Behavioral - Cultural Modeling and Prediction","author":"M-A Abbasi","year":"2012","unstructured":"Abbasi, M.-A., Kumar, S., Filho, J.A.A., Liu, H.: Lessons learned in using social media for disaster relief - ASU Crisis Response Game. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds.) SBP 2012. LNCS, vol. 7227, pp. 282\u2013289. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-29047-3_34"},{"key":"13_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1007\/978-3-642-37210-0_52","volume-title":"Social Computing, Behavioral-Cultural Modeling and Prediction","author":"S Chandan","year":"2013","unstructured":"Chandan, S., et al.: Modeling the interaction between emergency communications and behavior in the aftermath of a disaster. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds.) SBP 2013. LNCS, vol. 7812, pp. 476\u2013485. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-37210-0_52"},{"issue":"4","key":"13_CR7","doi-asserted-by":"publisher","first-page":"e33285","DOI":"10.1371\/journal.pone.0033285","volume":"7","author":"N Petrovic","year":"2012","unstructured":"Petrovic, N., Alderson, D.L., Carlson, J.M.: Dynamic resource allocation in disaster response: tradeoffs in wildfire suppression. PloS one 7(4), e33285 (2012)","journal-title":"PloS one"},{"key":"13_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1007\/978-3-319-60240-0_5","volume-title":"Social, Cultural, and Behavioral Modeling","author":"MRJE Estuar","year":"2017","unstructured":"Estuar, M.R.J.E., Rodrigueza, R.C., Victorino, J.N.C., Sevilla, M.C.V., De Leon, M.M., Rosales, J.C.S.: Agent-Based modeling approach in understanding behavior during disasters: measuring response and rescue in eBayanihan disaster management platform. In: Lee, D., Lin, Y.-R., Osgood, N., Thomson, R. (eds.) SBP-BRiMS 2017. LNCS, vol. 10354, pp. 46\u201352. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-60240-0_5"},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.artint.2018.01.002","volume":"258","author":"SV Albrecht","year":"2018","unstructured":"Albrecht, S.V., Stone, P.: Autonomous agents modelling other agents: a comprehensive survey and open problems. Artif. Intell. 258, 66\u201395 (2018)","journal-title":"Artif. Intell."},{"key":"13_CR10","unstructured":"Yang, F., Liu, B., Dong, W.: Optimal control of complex systems through variational inference with a discrete event decision process. In: Proceedings of the 2019 International Conference on Autonomous Agents and Multiagent Systems, International Foundation for Autonomous Agents and Multiagent Systems (2019)"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Yang, F., Dong, W.: Integrating simulation and signal processing in tracking complex social systems. Comput. Math. Organ. Theor. 1\u201322 (2018). Special Issue: SBP-BRIMS2017","DOI":"10.1007\/s10588-018-9276-6"},{"key":"13_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/978-3-319-60240-0_23","volume-title":"Social, Cultural, and Behavioral Modeling","author":"F Yang","year":"2017","unstructured":"Yang, F., Dong, W.: Integrating simulation and signal processing with stochastic social kinetic model. In: Lee, D., Lin, Y.-R., Osgood, N., Thomson, R. (eds.) SBP-BRiMS 2017. LNCS, vol. 10354, pp. 193\u2013203. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-60240-0_23"},{"key":"13_CR13","unstructured":"Peng, P., et al.: Multiagent bidirectionally-coordinated nets for learning to play starcraft combat games, arXiv preprint arXiv:1703.10069 (2017)"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Matignon, L., Jeanpierre, L., Mouaddib, A.-I.: Coordinated multi-robot exploration under communication constraints using decentralized Markov decision processes. In: Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, pp. 2017\u20132023. AAAI Press (2012)","DOI":"10.1609\/aaai.v26i1.8380"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Ye, H., Li, G.Y., Juang, B.-H.F.: Deep reinforcement learning based resource allocation for V2V communications, arXiv preprint arXiv:1805.07222 (2018)","DOI":"10.1109\/ICC.2018.8422586"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Mirzaei, H., Sharon, G., Boyles, S., Givargis, T., Stone, P.: Enhanced delta-tolling: traffic optimization via policy gradient reinforcement learning. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 47\u201352. IEEE (2018)","DOI":"10.1109\/ITSC.2018.8569737"},{"key":"13_CR17","unstructured":"Albrecht, S.V., Ramamoorthy, S.: A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, International Foundation for Autonomous Agents and Multiagent Systems, pp. 1155\u20131156 (2013)"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Peters, J., Schaal, S.: Policy gradient methods for robotics. In: 2006 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 2219\u20132225. IEEE (2006)","DOI":"10.1109\/IROS.2006.282564"},{"key":"13_CR19","unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., Klimov, O.: Proximal policy optimization algorithms, arXiv preprint arXiv:1707.06347 (2017)"}],"container-title":["Lecture Notes in Computer Science","Social, Cultural, and Behavioral Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-21741-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T17:36:47Z","timestamp":1709833007000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-21741-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030217402","9783030217419"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-21741-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"5 June 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SBP-BRiMS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Washington, WA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sbp2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/sbp-brims.org\/2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}