{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T18:06:53Z","timestamp":1743012413767,"version":"3.40.3"},"publisher-location":"Cham","reference-count":8,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030627423"},{"type":"electronic","value":"9783030627430"}],"license":[{"start":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T00:00:00Z","timestamp":1604448000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T00:00:00Z","timestamp":1604448000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-62743-0_111","type":"book-chapter","created":{"date-parts":[[2020,11,3]],"date-time":"2020-11-03T06:02:58Z","timestamp":1604383378000},"page":"779-784","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Probability Programming and Control of Moving Agent Based on MC-POMDP"],"prefix":"10.1007","author":[{"given":"Yongyong","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinghua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,4]]},"reference":[{"issue":"4","key":"111_CR1","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1109\/MCOM.2019.1800603","volume":"57","author":"L Zhao","year":"2019","unstructured":"Zhao, L., Wang, J., Liu, J., et al.: Routing for crowd management in smart cities: a deep reinforcement learning perspective. IEEE Commun. Mag. 57(4), 88\u201393 (2019)","journal-title":"IEEE Commun. Mag."},{"issue":"99","key":"111_CR2","first-page":"1","volume":"PP","author":"C Wang","year":"2019","unstructured":"Wang, C., Ju, P., Lei, S., et al.: Markov decision process-based resilience enhancement for distribution systems: an approximate dynamic programming approach. IEEE Trans. Smart Grid PP(99), 1 (2019)","journal-title":"IEEE Trans. Smart Grid"},{"key":"111_CR3","unstructured":"Heydari, A.: Stability analysis of optimal adaptive control under value iteration using a stabilizing initial policy. IEEE Trans. Neural Netw. Learn. Syst. 29(9), 4522\u20134527 (2018)"},{"key":"111_CR4","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.inffus.2018.01.002","volume":"45","author":"J L\u00f3pez-Araquistain","year":"2018","unstructured":"L\u00f3pez-Araquistain, J., Jarama, \u00c1.J., Besada, J.A., et al.: A new approach to map-assisted Bayesian tracking filtering. Inf. Fusion 45, 79\u201395 (2018)","journal-title":"Inf. Fusion"},{"issue":"7","key":"111_CR5","doi-asserted-by":"crossref","first-page":"3140","DOI":"10.1109\/TNNLS.2017.2712823","volume":"29","author":"D Wang","year":"2017","unstructured":"Wang, D., Tan, X.: Bayesian neighborhood component analysis. IEEE Trans. Neural Netw. Learn. Syst. 29(7), 3140\u20133151 (2017)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"111_CR6","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.proeng.2017.12.137","volume":"211","author":"HN Chen","year":"2018","unstructured":"Chen, H.N., Mao, Z.L.: Study on the failure probability of occupant evacuation with the method of Monte Carlo sampling. Procedia Eng. 211, 55\u201362 (2018)","journal-title":"Procedia Eng."},{"key":"111_CR7","doi-asserted-by":"crossref","unstructured":"Kragic, D.: From active perception to deep learning. Sci. Robot. 3(23), eaav1778 (2018)","DOI":"10.1126\/scirobotics.aav1778"},{"key":"111_CR8","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1038\/s42256-019-0025-4","volume":"1","author":"EO Neftci","year":"2019","unstructured":"Neftci, E.O., Averbeck, B.B.: Reinforcement learning in artificial and biological systems. Nat. Mach. Intell. 1, 133\u2013143 (2019)","journal-title":"Nat. Mach. Intell."}],"container-title":["Advances in Intelligent Systems and Computing","The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-62743-0_111","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T09:00:28Z","timestamp":1669453228000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-62743-0_111"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,4]]},"ISBN":["9783030627423","9783030627430"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-62743-0_111","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2020,11,4]]},"assertion":[{"value":"4 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SPIOT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"spiot2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/spiot2020.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}