{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:48:58Z","timestamp":1740098938305,"version":"3.37.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319671895"},{"type":"electronic","value":"9783319671901"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-67190-1_17","type":"book-chapter","created":{"date-parts":[[2017,9,18]],"date-time":"2017-09-18T09:48:49Z","timestamp":1505728129000},"page":"222-235","source":"Crossref","is-referenced-by-count":2,"title":["LiMa: Sequential Lifted Marginal Filtering on Multiset State Descriptions"],"prefix":"10.1007","author":[{"given":"Max","family":"Schr\u00f6der","sequence":"first","affiliation":[]},{"given":"Stefan","family":"L\u00fcdtke","sequence":"additional","affiliation":[]},{"given":"Sebastian","family":"Bader","sequence":"additional","affiliation":[]},{"given":"Frank","family":"Kr\u00fcger","sequence":"additional","affiliation":[]},{"given":"Thomas","family":"Kirste","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,19]]},"reference":[{"key":"17_CR1","unstructured":"Ahmadi, B., Kersting, K., Sanner, S.: Multi-evidence lifted message passing, with application to pagerank and the kalman filter. In: Proceedings-International Joint Conference on Artificial Intelligence, p. 1152 (2011)"},{"issue":"3","key":"17_CR2","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.cognition.2009.07.005","volume":"113","author":"CL Baker","year":"2009","unstructured":"Baker, C.L., Saxe, R., Tenenbaum, J.B.: Action understanding as inverse planning. Cognition 113(3), 329\u2013349 (2009)","journal-title":"Cognition"},{"issue":"1","key":"17_CR3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3233\/FI-2011-575","volume":"112","author":"R Barbuti","year":"2011","unstructured":"Barbuti, R., Levi, F., Milazzo, P., Scatena, G.: Maximally parallel probabilistic semantics for multiset rewriting. Fundam. Inform. 112(1), 1\u201317 (2011)","journal-title":"Fundam. Inform."},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Berry, G., Boudol, G.: The chemical abstract machine. In: POPL, pp. 81\u201394. ACM, San Francisco(1990)","DOI":"10.1145\/96709.96717"},{"key":"17_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1007\/978-3-540-45210-2_38","volume-title":"Computer Aided Systems Theory - EUROCAST 2003","author":"S Bistarelli","year":"2003","unstructured":"Bistarelli, S., Cervesato, I., Lenzini, G., Marangoni, R., Martinelli, F.: On representing biological systems through multiset rewriting. In: Moreno-D\u00edaz, R., Pichler, F. (eds.) EUROCAST 2003. LNCS, vol. 2809, pp. 415\u2013426. Springer, Heidelberg (2003). doi: 10.1007\/978-3-540-45210-2_38"},{"key":"17_CR6","unstructured":"Boutilier, C., Reiter, R., Price, B.: Symbolic dynamic programming for first-order MDPs. In: Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, vol. 1, pp. 690\u2013700 (2001)"},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Choi, J., Amir, E., Xu, T., Valocchi, A.J.: Learning relational kalman filtering. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp. 2539\u20132546 (2015)","DOI":"10.1609\/aaai.v29i1.9633"},{"key":"17_CR8","unstructured":"Choi, J., Hill, D.J., Amir, E.: Lifted inference for relational continuous models. In: Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, UAI 2010, pp. 126\u2013134. AUAI Press (2010)"},{"issue":"3","key":"17_CR9","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1109\/MPRV.2003.1228524","volume":"2","author":"V Fox","year":"2003","unstructured":"Fox, V., Hightower, J., Liao, L., Schulz, D., Borriello, G.: Bayesian filtering for location estimation. IEEE Pervasive Comput. 2(3), 24\u201333 (2003)","journal-title":"IEEE Pervasive Comput."},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Geier, T., Biundo, S.: Approximate online inference for dynamic Markov logic networks. In: 23rd IEEE International Conference on Tools with Artificial Intelligence, pp. 764\u2013768. IEEE (2011)","DOI":"10.1109\/ICTAI.2011.120"},{"key":"17_CR11","unstructured":"Huang, J., Guestrin, C., Jiang, X., Guibas, L.: Exploiting probabilistic independence for permutations. In: AISTATS, Clearwater, USA, pp. 248\u2013255 (2009)"},{"key":"17_CR12","unstructured":"Kersting, K., Ahmadi, B., Natarajan, S.: Counting belief propagation. In: UAI, Montreal, Canada, pp. 277\u2013284 (2009)"},{"key":"17_CR13","unstructured":"Kersting, K.: Lifted probabilistic inference. In: 20th European Conference on Artificial Intelligence, ECAI 2012. Frontiers in Artificial Intelligence and Applications, vol. 242. IOS Press (2012)"},{"key":"17_CR14","unstructured":"Khardon, R., Sanner, S.: Stochastic planning and lifted inference. arXiv preprint arXiv:1701.01048 (2017)"},{"key":"17_CR15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10994-014-5443-2","volume":"99","author":"A Kimmig","year":"2015","unstructured":"Kimmig, A., Mihalkova, L., Getoor, L.: Lifted graphical models: a survey. Mach. Learn. 99, 1\u201345 (2015)","journal-title":"Mach. Learn."},{"key":"17_CR16","unstructured":"Kondor, R., Howard, A., Jebara, T.: Multi-object tracking with representations of the symmetric group. In: AISTATS, vol. 2, pp. 211\u2013218 (2007)"},{"issue":"11","key":"17_CR17","doi-asserted-by":"crossref","first-page":"e109381","DOI":"10.1371\/journal.pone.0109381","volume":"9","author":"F Kr\u00fcger","year":"2014","unstructured":"Kr\u00fcger, F., Nyolt, M., Yordanova, K., Hein, A., Kirste, T.: Computational state space models for activity and intention recognition. A feasibility study. PLOS ONE 9(11), e109381 (2014)","journal-title":"PLOS ONE"},{"key":"17_CR18","unstructured":"Poole, D.: First-order probabilistic inference. In: IJCAI, pp. 985\u2013991 (2003)"},{"key":"17_CR19","unstructured":"Ram\u00edrez, M., Geffner, H.: Goal recognition over POMDPs: inferring the intention of a POMDP agent. In: Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, pp. 2009\u20132014, July 2011"},{"key":"17_CR20","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1016\/j.artint.2008.11.003","volume":"173","author":"S Sanner","year":"2009","unstructured":"Sanner, S., Boutilier, C.: Practical solution techniques for first-order MDPs. Artif. Intell. 173, 748\u2013788 (2009)","journal-title":"Artif. Intell."},{"key":"17_CR21","unstructured":"Schr\u00f6der, M., L\u00fcdtke, S., Bader, S., Kr\u00fcger, F., Kirste, T.: An office scenario dataset for benchmarking observation-equivalent entities (2016). http:\/\/dx.doi.org\/10.18453\/rosdok_id00000138"},{"key":"17_CR22","unstructured":"Schr\u00f6der, M., L\u00fcdtke, S., Bader, S., Kr\u00fcger, F., Kirste, T.: Abstracting from observation-equivalent entities in human behavior modeling. In: AAAI Workshop: Plan, Activity, and Intent Recognition, February 2017"},{"key":"17_CR23","unstructured":"Van Den Broeck, G., Taghipour, N., Meert, W., Davis, J., De Raedt, L.: Lifted probabilistic inference by first-order knowledge compilation. In: IJCAI, pp. 2178\u20132185 (2011)"},{"key":"17_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1007\/978-3-662-44845-8_17","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"D Venugopal","year":"2014","unstructured":"Venugopal, D., Gogate, V.: Evidence-based clustering for scalable inference in Markov logic. In: Calders, T., Esposito, F., H\u00fcllermeier, E., Meo, R. (eds.) ECML PKDD 2014. LNCS, vol. 8726, pp. 258\u2013273. Springer, Heidelberg (2014). doi: 10.1007\/978-3-662-44845-8_17"},{"key":"17_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1007\/11428572_5","volume-title":"Pervasive Computing","author":"DH Wilson","year":"2005","unstructured":"Wilson, D.H., Atkeson, C.: Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) Pervasive 2005. LNCS, vol. 3468, pp. 62\u201379. Springer, Heidelberg (2005). doi: 10.1007\/11428572_5"}],"container-title":["Lecture Notes in Computer Science","KI 2017: Advances in Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-67190-1_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T23:13:35Z","timestamp":1659482015000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-67190-1_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319671895","9783319671901"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-67190-1_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}