{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T02:36:52Z","timestamp":1743129412562,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030959029"},{"type":"electronic","value":"9783030959036"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-95903-6_44","type":"book-chapter","created":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T13:03:32Z","timestamp":1643720612000},"page":"417-429","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Performance Evaluation of a DQN-Based Autonomous Aerial Vehicle Mobility Control Method in an Indoor Single-Path Environment with a Staircase"],"prefix":"10.1007","author":[{"given":"Nobuki","family":"Saito","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tetsuya","family":"Oda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aoto","family":"Hirata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chihiro","family":"Yukawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masaharu","family":"Hirota","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leonard","family":"Barolli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,2]]},"reference":[{"issue":"5","key":"44_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/rs9050459","volume":"9","author":"C St\u00f6cker","year":"2017","unstructured":"St\u00f6cker, C., et al.: Review of the current state of UAV regulations. Remote Sens. 9(5), 1\u201326 (2017)","journal-title":"Remote Sens."},{"key":"44_CR2","doi-asserted-by":"crossref","unstructured":"Artemenko, O., et al.: Energy-aware trajectory planning for the localization of mobile devices using an unmanned aerial vehicle. In: Proceedings of the 25-th International Conference on Computer Communication and Networks (ICCCN-2016), pp. 1\u20139 (2016)","DOI":"10.1109\/ICCCN.2016.7568517"},{"key":"44_CR3","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1007\/s10514-020-09903-2","volume":"44","author":"M Popovi\u0107","year":"2020","unstructured":"Popovi\u0107, M., et al.: An informative path planning framework for UAV-based terrain monitoring. Auton. Robot. 44, 889\u2013911 (2020)","journal-title":"Auton. Robot."},{"key":"44_CR4","doi-asserted-by":"crossref","unstructured":"Nguyen, H., et al.: LAVAPilot: lightweight UAV trajectory planner with situational awareness for embedded autonomy to track and locate radio-tags. arXiv:2007.15860, pp. 1\u20138 (2020)","DOI":"10.1109\/IROS45743.2020.9341615"},{"key":"44_CR5","doi-asserted-by":"crossref","unstructured":"Oda, T., et al.: Design and implementation of a simulation system based on deep Q-network for mobile actor node control in wireless sensor and actor networks. In: Proceedings of the 31-th IEEE International Conference on Advanced Information Networking and Applications Workshops (IEEE AINA-2017), pp. 195\u2013200 (2017)","DOI":"10.1109\/WAINA.2017.67"},{"key":"44_CR6","series-title":"Lecture Notes on Data Engineering and Communications Technologies","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/978-3-319-65636-6_4","volume-title":"Advances in Intelligent Networking and Collaborative Systems","author":"T Oda","year":"2018","unstructured":"Oda, T., Elmazi, D., Cuka, M., Kulla, E., Ikeda, M., Barolli, L.: Performance evaluation of a deep Q-network based simulation system for actor node mobility control in wireless sensor and actor networks considering three-dimensional environment. In: Barolli, L., Woungang, I., Hussain, O.K. (eds.) INCoS 2017. LNDECT, vol. 8, pp. 41\u201352. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-65636-6_4"},{"key":"44_CR7","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1007\/978-3-319-93659-8_77","volume-title":"Complex, Intelligent, and Software Intensive Systems","author":"T Oda","year":"2019","unstructured":"Oda, T., Kulla, E., Katayama, K., Ikeda, M., Barolli, L.: A deep Q-network based simulation system for actor node mobility control in WSANs considering three-dimensional environment: a comparison study for normal and uniform distributions. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds.) CISIS 2018. AISC, vol. 772, pp. 842\u2013852. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-319-93659-8_77"},{"issue":"20","key":"44_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/rs12203386","volume":"12","author":"J Sandino","year":"2020","unstructured":"Sandino, J., et al.: UAV framework for autonomous onboard navigation and people\/object detection in cluttered indoor environments. Remote Sens. 12(20), 1\u201331 (2020)","journal-title":"Remote Sens."},{"key":"44_CR9","doi-asserted-by":"crossref","unstructured":"Moulton, J., et al.: An autonomous surface vehicle for long term operations. In: Proceedings of MTS\/IEEE OCEANS, pp. 1\u201310 (2018)","DOI":"10.1109\/OCEANS.2018.8604718"},{"key":"44_CR10","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1007\/978-3-030-15035-8_34","volume-title":"Web, Artificial Intelligence and Network Applications","author":"T Oda","year":"2019","unstructured":"Oda, T., Ueda, C., Ozaki, R., Katayama, K.: Design of a deep Q-network based simulation system for actuation decision in ambient intelligence. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) WAINA 2019. AISC, vol. 927, pp. 362\u2013370. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-15035-8_34"},{"issue":"2","key":"44_CR11","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1504\/IJWGS.2017.083384","volume":"13","author":"T Oda","year":"2017","unstructured":"Oda, T., et al.: Design and implementation of an IoT-based E-learning testbed. Int. J. Web Grid Serv. 13(2), 228\u2013241 (2017)","journal-title":"Int. J. Web Grid Serv."},{"key":"44_CR12","series-title":"Lecture Notes in Networks and Systems","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1007\/978-3-030-61108-8_44","volume-title":"Advances on Broad-Band Wireless Computing, Communication and Applications","author":"Y Hirota","year":"2021","unstructured":"Hirota, Y., Oda, T., Saito, N., Hirata, A., Hirota, M., Katatama, K.: Proposal and experimental results of an ambient intelligence for training on soldering iron holding. In: Barolli, L., Takizawa, M., Enokido, T., Chen, H.-C., Matsuo, K. (eds.) BWCCA 2020. LNNS, vol. 159, pp. 444\u2013453. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-61108-8_44"},{"key":"44_CR13","doi-asserted-by":"crossref","unstructured":"Hayosh, D., et al.: Woody: low-cost, open-source humanoid torso robot. In: Proceedings of the 17-th International Conference on Ubiquitous Robots (ICUR-2020), pp. 247\u2013252 (2020)","DOI":"10.1109\/UR49135.2020.9144924"},{"key":"44_CR14","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518, 529\u2013533 (2015)","journal-title":"Nature"},{"key":"44_CR15","unstructured":"Mnih, V., et al.: Playing Atari with deep reinforcement learning. arXiv:1312.5602, pp. 1\u20139 (2013)"},{"key":"44_CR16","unstructured":"Lei, T., Ming, L.: A robot exploration strategy based on Q-learning network. In: IEEE International Conference on Real-time Computing and Robotics (IEEE RCAR-2016), pp. 57\u201362 (2016)"},{"key":"44_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/11564096_32","volume-title":"Machine Learning: ECML 2005","author":"M Riedmiller","year":"2005","unstructured":"Riedmiller, M.: Neural fitted Q iteration \u2013 first experiences with a data efficient neural reinforcement learning method. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 317\u2013328. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11564096_32"},{"key":"44_CR18","unstructured":"Lin, L.J.: Reinforcement learning for robots using neural networks. In: Proceedings of Technical Report, DTIC Document (1993)"},{"key":"44_CR19","doi-asserted-by":"crossref","unstructured":"Lange, S., Riedmiller, M.: Deep auto-encoder neural networks in reinforcement learning. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN-2010), pp. 1\u20138 (2010)","DOI":"10.1109\/IJCNN.2010.5596468"},{"issue":"1\u20132","key":"44_CR20","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/S0004-3702(98)00023-X","volume":"101","author":"LP Kaelbling","year":"1998","unstructured":"Kaelbling, L.P., et al.: Planning and acting in partially observable stochastic domains. Artif. Intell. 101(1\u20132), 99\u2013134 (1998)","journal-title":"Artif. Intell."},{"key":"44_CR21","doi-asserted-by":"publisher","first-page":"100394","DOI":"10.1016\/j.iot.2021.100394","volume":"14","author":"N Saito","year":"2021","unstructured":"Saito, N., et al.: A Tabu list strategy based DQN for AAV mobility in indoor single-path environment: implementation and performance evaluation. Internet Things 14, 100394 (2021)","journal-title":"Internet Things"},{"key":"44_CR22","unstructured":"Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the 13-th International Conference on Artificial Intelligence and Statistics (AISTATS-2010), pp. 249\u2013256 (2010)"},{"key":"44_CR23","unstructured":"Glorot, X., et al.: Deep sparse rectifier neural networks. In: Proceedings of the 14-th International Conference on Artificial Intelligence and Statistics (AISTATS-2011), pp. 315\u2013323 (2011)"},{"issue":"3","key":"44_CR24","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1287\/ijoc.1.3.190","volume":"1","author":"F Glover","year":"1989","unstructured":"Glover, F.: Tabu search - part I. ORSA J. Comput. 1(3), 190\u2013206 (1989)","journal-title":"ORSA J. Comput."}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advances in Internet, Data &amp; Web Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-95903-6_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T13:09:38Z","timestamp":1643720978000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-95903-6_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030959029","9783030959036"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-95903-6_44","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"2 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EIDWT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Emerging Internetworking, Data & Web Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Okayama","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 February 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 February 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eidwt2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}