{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T17:01:34Z","timestamp":1762102894914,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030192112"},{"type":"electronic","value":"9783030192129"}],"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"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-19212-9_33","type":"book-chapter","created":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T14:32:32Z","timestamp":1558362752000},"page":"502-518","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Metric Hybrid Factored Planning in Nonlinear Domains with Constraint Generation"],"prefix":"10.1007","author":[{"given":"Buser","family":"Say","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Scott","family":"Sanner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,4,28]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Agarwal, Y., Balaji, B., Gupta, R., Lyles, J., Wei, M., Weng, T.: Occupancy-driven energy management for smart building automation. In: ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building, pp. 1\u20136 (2010)","key":"33_CR1","DOI":"10.1145\/1878431.1878433"},{"issue":"1","key":"33_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1613\/jair.575","volume":"11","author":"C Boutilier","year":"1999","unstructured":"Boutilier, C., Dean, T., Hanks, S.: Decision-theoretic planning: structural assumptions and computational leverage. JAIR 11(1), 1\u201394 (1999). http:\/\/dl.acm.org\/citation.cfm?id=3013545.3013546","journal-title":"JAIR"},{"unstructured":"Bryce, D., Gao, S., Musliner, D., Goldman, R.: SMT-based nonlinear PDDL+ planning. In: 29th AAAI, pp. 3247\u20133253 (2015). http:\/\/dl.acm.org\/citation.cfm?id=2888116.2888168","key":"33_CR3"},{"unstructured":"Cashmore, M., Fox, M., Long, D., Magazzeni, D.: A compilation of the full PDDL+ language into SMT. In: ICAPS, pp. 79\u201387 (2016). http:\/\/dl.acm.org\/citation.cfm?id=3038594.3038605","key":"33_CR4"},{"key":"33_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1613\/jair.3608","volume":"44","author":"AJ Coles","year":"2012","unstructured":"Coles, A.J., Coles, A.I., Fox, M., Long, D.: COLIN: planning with continuous linear numeric change. JAIR 44, 1\u201396 (2012)","journal-title":"JAIR"},{"issue":"1","key":"33_CR6","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1613\/jair.2044","volume":"27","author":"M Fox","year":"2006","unstructured":"Fox, M., Long, D.: Modelling mixed discrete-continuous domains for planning. JAIR 27(1), 235\u2013297 (2006). http:\/\/dl.acm.org\/citation.cfm?id=1622572.1622580","journal-title":"JAIR"},{"unstructured":"Fox, M., Long, D., Magazzeni, D.: Plan-based policies for efficient multiple battery load management. CoRR abs\/1401.5859 (2014). http:\/\/arxiv.org\/abs\/1401.5859","key":"33_CR7"},{"doi-asserted-by":"publisher","unstructured":"Henzinger, T.A., Kopke, P.W., Puri, A., Varaiya, P.: What\u2019s decidable about hybrid automata? In: Proceedings of the Twenty-Seventh Annual ACM Symposium on Theory of Computing, pp. 373\u2013382. ACM, New York (1995). https:\/\/doi.org\/10.1145\/225058.225162 , http:\/\/doi.acm.org\/10.1145\/225058.225162","key":"33_CR8","DOI":"10.1145\/225058.225162"},{"unstructured":"L\u00f6hr, J., Eyerich, P., Keller, T., Nebel, B.: A planning based framework for controlling hybrid systems. In: ICAPS, pp. 164\u2013171 (2012). http:\/\/www.aaai.org\/ocs\/index.php\/ICAPS\/ICAPS12\/paper\/view\/4708","key":"33_CR9"},{"unstructured":"Maher, S.J., et al.: The SCIP optimization suite 4.0. Technical report 17-12, ZIB, Takustr. 7, 14195 Berlin (2017)","key":"33_CR10"},{"issue":"1","key":"33_CR11","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1287\/opre.18.1.24","volume":"18","author":"LGM Mitten","year":"1970","unstructured":"Mitten, L.G.M.: Branch-and-bound methods: general formulation and properties. Oper. Res. 18(1), 24\u201334 (1970). http:\/\/www.jstor.org\/stable\/168660","journal-title":"Oper. Res."},{"unstructured":"Penna, G.D., Magazzeni, D., Mercorio, F., Intrigila, B.: UPMurphi: a tool for universal planning on PDDL+ problems. In: ICAPS, pp. 106\u2013113 (2009). http:\/\/dl.acm.org\/citation.cfm?id=3037223.3037238","key":"33_CR12"},{"unstructured":"Piotrowski, W.M., Fox, M., Long, D., Magazzeni, D., Mercorio, F.: Heuristic planning for hybrid systems. In: AAAI, pp. 4254\u20134255 (2016). http:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI16\/paper\/view\/12394","key":"33_CR13"},{"doi-asserted-by":"crossref","unstructured":"Raghavan, A., Sanner, S., Tadepalli, P., Fern, A., Khardon, R.: Hindsight optimization for hybrid state and action MDPs. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, USA (2017)","key":"33_CR14","DOI":"10.1609\/aaai.v31i1.11056"},{"unstructured":"Sanner, S.: Relational dynamic influence diagram language (RDDL): Language description (2010)","key":"33_CR15"},{"doi-asserted-by":"publisher","unstructured":"Say, B., Wu, G., Zhou, Y.Q., Sanner, S.: Nonlinear hybrid planning with deep net learned transition models and mixed-integer linear programming. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, pp. 750\u2013756 (2017). https:\/\/doi.org\/10.24963\/ijcai.2017\/104","key":"33_CR16","DOI":"10.24963\/ijcai.2017\/104"},{"doi-asserted-by":"publisher","unstructured":"Scala, E., Haslum, P., Thi\u00e9baux, S., Ram\u00edrez, M.: Interval-based relaxation for general numeric planning. In: ECAI, pp. 655\u2013663 (2016). https:\/\/doi.org\/10.3233\/978-1-61499-672-9-655","key":"33_CR17","DOI":"10.3233\/978-1-61499-672-9-655"},{"issue":"1\u20132","key":"33_CR18","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.artint.2005.04.001","volume":"166","author":"JA Shin","year":"2005","unstructured":"Shin, J.A., Davis, E.: Processes and continuous change in a sat-based planner. Artif. Intell. 166(1\u20132), 194\u2013253 (2005). https:\/\/doi.org\/10.1016\/j.artint.2005.04.001","journal-title":"Artif. Intell."},{"unstructured":"Wu, G., Say, B., Sanner, S.: Scalable planning with tensorflow for hybrid nonlinear domains. In: Proceedings of the Thirty First Annual Conference on Advances in Neural Information Processing Systems (NIPS 2017), Long Beach, CA (2017)","key":"33_CR19"}],"container-title":["Lecture Notes in Computer Science","Integration of Constraint Programming, Artificial Intelligence, and Operations Research"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-19212-9_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,18]],"date-time":"2022-09-18T09:05:35Z","timestamp":1663491935000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-19212-9_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030192112","9783030192129"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-19212-9_33","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":"28 April 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CPAIOR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thessaloniki","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","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":"4 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 June 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cpaior2019b","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cpaior2019.uowm.gr\/","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"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"94","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"34","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"9","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"36% - 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"}},{"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"}},{"value":"5.67","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}