{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T00:25:45Z","timestamp":1778199945408,"version":"3.51.4"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030865160","type":"print"},{"value":"9783030865177","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-86517-7_11","type":"book-chapter","created":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T10:08:05Z","timestamp":1631182085000},"page":"168-181","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Action Set Based Policy Optimization for Safe Power Grid Management"],"prefix":"10.1007","author":[{"given":"Bo","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongsheng","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuecheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kejiao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,10]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Bernard, S., Trudel, G., Scott, G.: A 735 kV shunt reactors automatic switching system for hydro-Quebec network. IEEE Trans. Power Syst. 11(CONF-960111-), 2024\u20132030 (1996)","DOI":"10.1109\/59.544680"},{"key":"11_CR2","unstructured":"Bishop, C.M.: Pattern Recognition and Machine Learning. Information Science and Statistics. Springer, New York (2006)"},{"key":"11_CR3","unstructured":"Brockman, G., et al.: Openai gym. arXiv preprint arXiv:1606.01540 (2016)"},{"key":"11_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1007\/978-3-540-75538-8_7","volume-title":"Computers and Games","author":"R Coulom","year":"2007","unstructured":"Coulom, R.: Efficient selectivity and backup operators in Monte-Carlo tree search. In: van den Herik, H.J., Ciancarini, P., Donkers, H.H.L.M.J. (eds.) CG 2006. LNCS, vol. 4630, pp. 72\u201383. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-75538-8_7"},{"key":"11_CR5","unstructured":"Dalal, G., Gilboa, E., Mannor, S.: Hierarchical decision making in electricity grid management. In: International Conference on Machine Learning, pp. 2197\u20132206 (2016)"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Diao, R., Wang, Z., Shi, D., Chang, Q., Duan, J., Zhang, X.: Autonomous voltage control for grid operation using deep reinforcement learning. In: 2019 IEEE Power & Energy Society General Meeting (PESGM), pp. 1\u20135. IEEE (2019)","DOI":"10.1109\/PESGM40551.2019.8973924"},{"key":"11_CR7","unstructured":"Eigen, M.: Ingo rechenberg evolutionsstrategie optimierung technischer systeme nach prinzipien der biologishen evolution. In: mit einem Nachwort von Manfred Eigen, vol. 45, pp. 46\u201347 (1973)"},{"issue":"1","key":"11_CR8","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1109\/TPWRS.2003.821457","volume":"19","author":"D Ernst","year":"2004","unstructured":"Ernst, D., Glavic, M., Wehenkel, L.: Power systems stability control: reinforcement learning framework. IEEE Trans. Power Syst. 19(1), 427\u2013435 (2004)","journal-title":"IEEE Trans. Power Syst."},{"issue":"3","key":"11_CR9","doi-asserted-by":"publisher","first-page":"1346","DOI":"10.1109\/TPWRS.2008.922256","volume":"23","author":"EB Fisher","year":"2008","unstructured":"Fisher, E.B., O\u2019Neill, R.P., Ferris, M.C.: Optimal transmission switching. IEEE Trans. Power Syst. 23(3), 1346\u20131355 (2008)","journal-title":"IEEE Trans. Power Syst."},{"issue":"3","key":"11_CR10","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1016\/0005-1098(89)90002-2","volume":"25","author":"CE Garcia","year":"1989","unstructured":"Garcia, C.E., Prett, D.M., Morari, M.: Model predictive control: theory and practice-a survey. Automatica 25(3), 335\u2013348 (1989)","journal-title":"Automatica"},{"key":"11_CR11","unstructured":"Horgan, D., et al.: Distributed prioritized experience replay. In: International Conference on Learning Representations (2018). https:\/\/openreview.net\/forum?id=H1Dy--0Z"},{"issue":"2","key":"11_CR12","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.1109\/TSG.2019.2933191","volume":"11","author":"Q Huang","year":"2019","unstructured":"Huang, Q., Huang, R., Hao, W., Tan, J., Fan, R., Huang, Z.: Adaptive power system emergency control using deep reinforcement learning. IEEE Trans. Smart Grid 11(2), 1171\u20131182 (2019)","journal-title":"IEEE Trans. Smart Grid"},{"issue":"2","key":"11_CR13","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1109\/TPWRS.2009.2034748","volume":"25","author":"L Jin","year":"2009","unstructured":"Jin, L., Kumar, R., Elia, N.: Model predictive control-based real-time power system protection schemes. IEEE Trans. Power Syst. 25(2), 988\u2013998 (2009)","journal-title":"IEEE Trans. Power Syst."},{"issue":"4","key":"11_CR14","doi-asserted-by":"publisher","first-page":"1937","DOI":"10.1109\/TPWRS.2010.2046344","volume":"25","author":"A Khodaei","year":"2010","unstructured":"Khodaei, A., Shahidehpour, M.: Transmission switching in security-constrained unit commitment. IEEE Trans. Power Syst. 25(4), 1937\u20131945 (2010)","journal-title":"IEEE Trans. Power Syst."},{"issue":"2","key":"11_CR15","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/S0142-0615(01)00017-5","volume":"24","author":"M Larsson","year":"2002","unstructured":"Larsson, M., Hill, D.J., Olsson, G.: Emergency voltage control using search and predictive control. Int. J. Electr. Power Energy Syst. 24(2), 121\u2013130 (2002)","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., Hutter, M.: Learning quadrupedal locomotion over challenging terrain. Sci. Robot. 5(47), eabc5986 (2020)","DOI":"10.1126\/scirobotics.abc5986"},{"key":"11_CR17","doi-asserted-by":"publisher","first-page":"106635","DOI":"10.1016\/j.epsr.2020.106635","volume":"189","author":"A Marot","year":"2020","unstructured":"Marot, A., et al.: Learning to run a power network challenge for training topology controllers. Electr. Power Syst. Res. 189, 106635 (2020)","journal-title":"Electr. Power Syst. Res."},{"key":"11_CR18","unstructured":"Marot, A., et al.: L2RPN: learning to run a power network in a sustainable world NeurIPS2020 challenge design (2020)"},{"issue":"7540","key":"11_CR19","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(7540), 529\u2013533 (2015)","journal-title":"Nature"},{"issue":"4","key":"11_CR20","doi-asserted-by":"publisher","first-page":"2283","DOI":"10.1109\/TPWRS.2007.907589","volume":"22","author":"B Otomega","year":"2007","unstructured":"Otomega, B., Glavic, M., Van Cutsem, T.: Distributed undervoltage load shedding. IEEE Trans. Power Syst. 22(4), 2283\u20132284 (2007)","journal-title":"IEEE Trans. Power Syst."},{"key":"11_CR21","unstructured":"Salimans, T., Ho, J., Chen, X., Sidor, S., Sutskever, I.: Evolution strategies as a scalable alternative to reinforcement learning. arXiv preprint arXiv:1703.03864 (2017)"},{"issue":"7839","key":"11_CR22","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1038\/s41586-020-03051-4","volume":"588","author":"J Schrittwieser","year":"2020","unstructured":"Schrittwieser, J., et al.: Mastering atari, go, chess and shogi by planning with a learned model. Nature 588(7839), 604\u2013609 (2020)","journal-title":"Nature"},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"Schwefel, H.P.: Numerische optimierung von computer-modellen mittels der evolutionsstrategie. (Teil 1, Kap. 1\u20135). Birkh\u00e4user (1977)","DOI":"10.1007\/978-3-0348-5927-1_1"},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"Shah, S., Arunesh, S., Pradeep, V., Andrew, P., Milind, T.: Solving online threat screening games using constrained action space reinforcement learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 2226\u20132235 (2020)","DOI":"10.1609\/aaai.v34i02.5599"},{"issue":"7587","key":"11_CR25","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1038\/nature16961","volume":"529","author":"D Silver","year":"2016","unstructured":"Silver, D., et al.: Mastering the game of go with deep neural networks and tree search. Nature 529(7587), 484\u2013489 (2016)","journal-title":"Nature"},{"key":"11_CR26","volume-title":"Reinforcement Learning: An Introduction","author":"RS Sutton","year":"2018","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (2018)"},{"issue":"5","key":"11_CR27","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/JPROC.2005.847249","volume":"93","author":"K Tomsovic","year":"2005","unstructured":"Tomsovic, K., Bakken, D.E., Venkatasubramanian, V., Bose, A.: Designing the next generation of real-time control, communication, and computations for large power systems. Proc. IEEE 93(5), 965\u2013979 (2005)","journal-title":"Proc. IEEE"},{"issue":"3","key":"11_CR28","doi-asserted-by":"publisher","first-page":"958","DOI":"10.1109\/59.780908","volume":"14","author":"G Trudel","year":"1999","unstructured":"Trudel, G., Bernard, S., Scott, G.: Hydro-Quebec\u2019s defence plan against extreme contingencies. IEEE Trans. Power Syst. 14(3), 958\u2013965 (1999)","journal-title":"IEEE Trans. Power Syst."},{"issue":"3\u20134","key":"11_CR29","first-page":"279","volume":"8","author":"CJ Watkins","year":"1992","unstructured":"Watkins, C.J., Dayan, P.: Q-learning. Mach. Learn. 8(3\u20134), 279\u2013292 (1992)","journal-title":"Mach. Learn."},{"issue":"3","key":"11_CR30","doi-asserted-by":"publisher","first-page":"2313","DOI":"10.1109\/TSG.2019.2951769","volume":"11","author":"Q Yang","year":"2019","unstructured":"Yang, Q., Wang, G., Sadeghi, A., Giannakis, G.B., Sun, J.: Two-timescale voltage control in distribution grids using deep reinforcement learning. IEEE Trans. Smart Grid 11(3), 2313\u20132323 (2019)","journal-title":"IEEE Trans. Smart Grid"},{"key":"11_CR31","unstructured":"Yoon, D., Hong, S., Lee, B.J., Kim, K.E.: Winning the L2RPN challenge: power grid management via semi-Markov afterstate actor-critic. In: International Conference on Learning Representations (2021). https:\/\/openreview.net\/forum?id=LmUJqB1Cz8"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86517-7_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T22:09:01Z","timestamp":1757369341000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86517-7_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030865160","9783030865177"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86517-7_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"10 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bilbao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2021.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-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":"869","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":"210","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":"24% - 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":"3-4","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":"3-9","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)"}},{"value":"The conference was held online due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}