{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T03:07:19Z","timestamp":1743044839888,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031687372"},{"type":"electronic","value":"9783031687389"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-68738-9_35","type":"book-chapter","created":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T23:02:40Z","timestamp":1725836560000},"page":"438-445","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Neuro-Symbolic Artificial Intelligence for\u00a0Safety Engineering"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5896-4860","authenticated-orcid":false,"given":"Laura","family":"Carnevali","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9663-1071","authenticated-orcid":false,"given":"Marco","family":"Lippi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,9]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Agha, G., Palmskog, K.: A survey of statistical model checking. ACM Trans. Model. Comput. Simul. (TOMACS) 28(1), 1\u201339 (2018)","key":"35_CR1","DOI":"10.1145\/3158668"},{"doi-asserted-by":"crossref","unstructured":"Badreddine, S., Garcez, A.d., Serafini, L., Spranger, M.: Logic tensor networks. Artif. Intell. 303, 103649 (2022)","key":"35_CR2","DOI":"10.1016\/j.artint.2021.103649"},{"unstructured":"Baier, C., Katoen, J.: Principles of Model Checking. MIT Press (2008)","key":"35_CR3"},{"issue":"4","key":"35_CR4","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1109\/THMS.2019.2903091","volume":"49","author":"M Biagi","year":"2019","unstructured":"Biagi, M., Carnevali, L., Paolieri, M., Patara, F., Vicario, E.: A continuous-time model-based approach for activity recognition in pervasive environments. IEEE Trans. Hum. Mach. Syst. 49(4), 293\u2013303 (2019)","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"issue":"2","key":"35_CR5","first-page":"1","volume":"3","author":"M Biagi","year":"2018","unstructured":"Biagi, M., Carnevali, L., Tarani, F., Vicario, E.: Model-based quantitative evaluation of repair procedures in gas distribution networks. ACM Trans. Cyber Phys. Sys. 3(2), 1\u201326 (2018)","journal-title":"ACM Trans. Cyber Phys. Sys."},{"issue":"3","key":"35_CR6","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/S0951-8320(00)00077-6","volume":"71","author":"A Bobbio","year":"2001","unstructured":"Bobbio, A., Portinale, L., Minichino, M., Ciancamerla, E.: Improving the analysis of dependable systems by mapping fault trees into bayesian networks. Reliab. Eng. Syst. Saf. 71(3), 249\u2013260 (2001)","journal-title":"Reliab. Eng. Syst. Saf."},{"unstructured":"Camacho, A., McIlraith, S.A.: Towards neural-guided program synthesis for linear temporal logic specifications. arXiv preprint arXiv:1912.13430 (2019)","key":"35_CR7"},{"issue":"9","key":"35_CR8","doi-asserted-by":"publisher","first-page":"4026","DOI":"10.3390\/app11094026","volume":"11","author":"L Carnevali","year":"2021","unstructured":"Carnevali, L., Ciani, L., Fantechi, A., Gori, G., Papini, M.: An efficient library for reliability block diagram evaluation. Appl. Sci. 11(9), 4026 (2021)","journal-title":"Appl. Sci."},{"doi-asserted-by":"crossref","unstructured":"Carnevali, L., Ridi, L., Vicario, E.: A quantitative approach to input generation in real-time testing of stochastic systems. IEEE Trans. Sw. Eng. 39(3), 292\u2013304 (2012)","key":"35_CR9","DOI":"10.1109\/TSE.2012.42"},{"doi-asserted-by":"crossref","unstructured":"Carnevali, L., Tarani, F., Vicario, E.: Performability evaluation of water distribution systems during maintenance procedures. IEEE Trans. Syst. Man Cybern. Syst. 50(5), 1704\u20131720 (2018)","key":"35_CR10","DOI":"10.1109\/TSMC.2017.2783188"},{"unstructured":"Chen, M., Zheng, A.X., Lloyd, J., Jordan, M.I., Brewer, E.: Failure diagnosis using decision trees. In: International Conference on Autonomic Computing, 2004. Proceedings, pp. 36\u201343. IEEE (2004)","key":"35_CR11"},{"doi-asserted-by":"crossref","unstructured":"Chen, Y., Nielsen, T.D.: Active learning of Markov decision processes for system verification. In: 2012 11th International Conference on Machine Learning and Applications, vol. 2, pp. 289\u2013294. IEEE (2012)","key":"35_CR12","DOI":"10.1109\/ICMLA.2012.158"},{"issue":"7","key":"35_CR13","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1109\/32.297939","volume":"20","author":"G Ciardo","year":"1994","unstructured":"Ciardo, G., German, R., Lindemann, C.: A characterization of the stochastic process underlying a stochastic petri net. IEEE Trans. Softw. Eng. 20(7), 506\u2013515 (1994)","journal-title":"IEEE Trans. Softw. Eng."},{"issue":"6","key":"35_CR14","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1109\/TSE.2012.67","volume":"39","author":"M Cinque","year":"2012","unstructured":"Cinque, M., Cotroneo, D., Pecchia, A.: Event logs for the analysis of software failures: a rule-based approach. IEEE Trans. Softw. Eng. 39(6), 806\u2013821 (2012)","journal-title":"IEEE Trans. Softw. Eng."},{"issue":"4","key":"35_CR15","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1145\/242223.242257","volume":"28","author":"EM Clarke","year":"1996","unstructured":"Clarke, E.M., Wing, J.M.: Formal methods: state of the art and future directions. ACM Comput. Surv. (CSUR) 28(4), 626\u2013643 (1996)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"35_CR16","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.artint.2015.08.011","volume":"244","author":"M Diligenti","year":"2017","unstructured":"Diligenti, M., Gori, M., Sacca, C.: Semantic-based regularization for learning and inference. Artif. Intell. 244, 143\u2013165 (2017)","journal-title":"Artif. Intell."},{"key":"35_CR17","doi-asserted-by":"publisher","DOI":"10.4324\/9781315807058","volume-title":"The Symbolic and Connectionist Paradigms: Closing The Gap","author":"J Dinsmore","year":"2014","unstructured":"Dinsmore, J.: The Symbolic and Connectionist Paradigms: Closing The Gap. Press, Psych (2014)"},{"unstructured":"Garcez, A.d., et al.: Neural-symbolic learning and reasoning: a survey and interpretation. Neuro Symbolic Artif. Intell. 342(1), 327 (2022)","key":"35_CR18"},{"issue":"3","key":"35_CR19","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1162\/neco.1992.4.3.393","volume":"4","author":"CL Giles","year":"1992","unstructured":"Giles, C.L., Miller, C.B., Chen, D., Chen, H.H., Sun, G.Z., Lee, Y.C.: Learning and extracting finite state automata with second-order recurrent neural networks. Neural Comput. 4(3), 393\u2013405 (1992)","journal-title":"Neural Comput."},{"doi-asserted-by":"crossref","unstructured":"Gulwani, S., Polozov, O., Singh, R., et al.: Program synthesis. Found. Trends\u00ae Program. Lang. 4(1-2), 1\u2013119 (2017)","key":"35_CR20","DOI":"10.1561\/2500000010"},{"doi-asserted-by":"crossref","unstructured":"Hitzler, P., Sarker, M.K.: Neuro-symbolic artificial intelligence: The state of the art (2022)","key":"35_CR21","DOI":"10.3233\/FAIA342"},{"doi-asserted-by":"crossref","unstructured":"Ivanov, R., Weimer, J., Alur, R., Pappas, G.J., Lee, I.: Verisig: verifying safety properties of hybrid systems with neural network controllers. In: Proceedings of the 22nd ACM International Conference on Hybrid Systems: Computation and Control, pp. 169\u2013178 (2019)","key":"35_CR22","DOI":"10.1145\/3302504.3311806"},{"doi-asserted-by":"publisher","unstructured":"Junges, S., Jansen, N., Dehnert, C., Topcu, U., Katoen, J.P.: Safety-constrained reinforcement learning for MDPs. In: Chechik, M., Raskin, J.F. (eds.) Tools and Algorithms for the Construction and Analysis of Systems. TACAS 2016. Lecture Notes in Computer Science, vol. 9636. Springer, Berlin, Heidelberg (2016). https:\/\/doi.org\/10.1007\/978-3-662-49674-9_8","key":"35_CR23","DOI":"10.1007\/978-3-662-49674-9_8"},{"doi-asserted-by":"crossref","unstructured":"Kwiatkowska, M.: Advances and challenges of quantitative verification and synthesis for cyber-physical systems. In: 2016 Science of Security for Cyber-Physical Systems Workshop (SOSCYPS), pp. 1\u20135. IEEE, New York, NY, USA (2016)","key":"35_CR24","DOI":"10.1109\/SOSCYPS.2016.7579999"},{"doi-asserted-by":"publisher","unstructured":"Kwiatkowska, M., Norman, G., Parker, D.: Stochastic model checking. In: Bernardo, M., Hillston, J. (eds.) Formal Methods for Performance Evaluation. SFM 2007. Lecture Notes in Computer Science, vol. 4486. Springer, Berlin, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-72522-0_6","key":"35_CR25","DOI":"10.1007\/978-3-540-72522-0_6"},{"doi-asserted-by":"publisher","unstructured":"Legay, A., Delahaye, B., Bensalem, S.: Statistical model checking: an overview. In: Barringer, H., et al. Runtime Verification. RV 2010. Lecture Notes in Computer Science, vol. 6418. Springer, Berlin, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-16612-9_11","key":"35_CR26","DOI":"10.1007\/978-3-642-16612-9_11"},{"unstructured":"Manhaeve, R., Dumancic, S., Kimmig, A., Demeester, T., De Raedt, L.: Deepproblog: neural probabilistic logic programming. Adv. NeurIPS 31 (2018)","key":"35_CR27"},{"doi-asserted-by":"crossref","unstructured":"Marra, G., Duman\u010di\u0107, S., Manhaeve, R., De Raedt, L.: From statistical relational to neurosymbolic artificial intelligence: a survey. Art. Int. 104062 (2024)","key":"35_CR28","DOI":"10.1016\/j.artint.2023.104062"},{"doi-asserted-by":"crossref","unstructured":"Perez-Cerrolaza, J., et al.: Artificial intelligence for safety-critical systems in industrial and transportation domains: a survey. ACM Comput. Surv. 56(7), 1\u201340 (2023)","key":"35_CR29","DOI":"10.1145\/3626314"},{"issue":"3","key":"35_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1670679.1670680","volume":"42","author":"F Salfner","year":"2010","unstructured":"Salfner, F., Lenk, M., Malek, M.: A survey of online failure prediction methods. ACM Comput. Surv. (CSUR) 42(3), 1\u201342 (2010)","journal-title":"ACM Comput. Surv. (CSUR)"},{"doi-asserted-by":"crossref","unstructured":"Sen, K., Viswanathan, M., Agha, G.: Learning continuous time Markov chains from sample executions. In: First International Conference on the Quantitative Evaluation of Systems, 2004. QEST 2004. Proceedings, pp. 146\u2013155. IEEE (2004)","key":"35_CR31","DOI":"10.1109\/QEST.2004.1348029"},{"issue":"1\u20132","key":"35_CR32","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/0004-3702(94)90105-8","volume":"70","author":"GG Towell","year":"1994","unstructured":"Towell, G.G., Shavlik, J.W.: Knowledge-based artificial neural networks. Artif. intell. 70(1\u20132), 119\u2013165 (1994)","journal-title":"Artif. intell."},{"issue":"2","key":"35_CR33","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1108\/IMDS-07-2021-0419","volume":"122","author":"Y Wang","year":"2022","unstructured":"Wang, Y., Chung, S.H.: Artificial intelligence in safety-critical systems: a systematic review. Ind. Manag. Data Syst. 122(2), 442\u2013470 (2022)","journal-title":"Ind. Manag. Data Syst."},{"unstructured":"Xu, J., Zhang, Z., Friedman, T., Liang, Y., Broeck, G.: A semantic loss function for deep learning with symbolic knowledge. In: International Conference on Machine Learning, pp. 5502\u20135511. PMLR (2018)","key":"35_CR34"}],"container-title":["Lecture Notes in Computer Science","Computer Safety, Reliability, and Security. SAFECOMP 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-68738-9_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T23:10:37Z","timestamp":1725837037000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-68738-9_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031687372","9783031687389"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-68738-9_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"9 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SAFECOMP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Safety, Reliability, and Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Florence","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"43","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"safecomp2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.safecomp2024.unifi.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}