{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T03:46:45Z","timestamp":1769831205247,"version":"3.49.0"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031723582","type":"print"},{"value":"9783031723599","type":"electronic"}],"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\/978-3-031-72359-9_21","type":"book-chapter","created":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T12:28:54Z","timestamp":1726662534000},"page":"285-298","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Learning Low-Level Causal Relations Using a\u00a0Simulated Robotic Arm"],"prefix":"10.1007","author":[{"given":"Miroslav","family":"Cibula","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthias","family":"Kerzel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3503-2080","authenticated-orcid":false,"given":"Igor","family":"Farka\u0161","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,18]]},"reference":[{"issue":"5","key":"21_CR1","doi-asserted-by":"publisher","first-page":"1402","DOI":"10.1162\/neco_a_01383","volume":"33","author":"A Ciria","year":"2021","unstructured":"Ciria, A., Schillaci, G., Pezzulo, G., Hafner, V.V., Lara, B.: Predictive processing in cognitive robotics: a review. Neural Comput. 33(5), 1402\u20131432 (2021). https:\/\/doi.org\/10.1162\/neco_a_01383","journal-title":"Neural Comput."},{"key":"21_CR2","unstructured":"Dillon, E., LaRiviere, J., Lundberg, S., Roth, J., Syrgkanis, V.: Be careful when interpreting predictive models in search of causal insights (2021). https:\/\/towardsdatascience.com\/be-careful-when-interpreting-predictive-models-in-search-of-causal-insights-e68626e664b6"},{"issue":"5","key":"21_CR3","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2001","unstructured":"Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Ann. Stat. 29(5), 1189\u20131232 (2001). https:\/\/doi.org\/10.1214\/aos\/1013203451","journal-title":"Ann. Stat."},{"key":"21_CR4","doi-asserted-by":"publisher","unstructured":"Gerstenberg, T., Tenenbaum, J.B.: Intuitive theories. In: Waldmann, M.R. (ed.) The Oxford Handbook of Causal Reasoning, pp. 515\u2013548. Oxford University Press (2017). https:\/\/doi.org\/10.1093\/oxfordhb\/9780199399550.013.28","DOI":"10.1093\/oxfordhb\/9780199399550.013.28"},{"key":"21_CR5","doi-asserted-by":"publisher","unstructured":"Gilpin, L.H., Bau, D., Yuan, B.Z., Bajwa, A., Specter, M., Kagal, L.: Explaining explanations: an overview of interpretability of machine learning. In: 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), pp. 80\u201389. IEEE (2018). https:\/\/doi.org\/10.1109\/dsaa.2018.00018","DOI":"10.1109\/dsaa.2018.00018"},{"key":"21_CR6","doi-asserted-by":"publisher","unstructured":"G\u00e4rdenfors, P., Lombard, M.: Causal cognition, force dynamics and early hunting technologies. Front. Psychol. 9 (2018). https:\/\/doi.org\/10.3389\/fpsyg.2018.00087","DOI":"10.3389\/fpsyg.2018.00087"},{"issue":"1","key":"21_CR7","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1515\/pjbr-2021-0017","volume":"12","author":"T Hellstr\u00f6m","year":"2021","unstructured":"Hellstr\u00f6m, T.: The relevance of causation in robotics: a review, categorization, and analysis. Paladyn, J. Behav. Rob. 12(1), 238\u2013255 (2021). https:\/\/doi.org\/10.1515\/pjbr-2021-0017","journal-title":"Paladyn, J. Behav. Rob."},{"key":"21_CR8","doi-asserted-by":"publisher","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization (2014). https:\/\/doi.org\/10.48550\/ARXIV.1412.6980","DOI":"10.48550\/ARXIV.1412.6980"},{"key":"21_CR9","doi-asserted-by":"publisher","unstructured":"Lake, B.M., Ullman, T.D., Tenenbaum, J.B., Gershman, S.J.: Building machines that learn and think like people. Behav. Brain Sci. 40 (2016). https:\/\/doi.org\/10.1017\/s0140525x16001837","DOI":"10.1017\/s0140525x16001837"},{"key":"21_CR10","doi-asserted-by":"publisher","unstructured":"Lee, T.E., Zhao, J.A., Sawhney, A.S., Girdhar, S., Kroemer, O.: Causal reasoning in simulation for structure and transfer learning of robot manipulation policies. In: IEEE International Conference on Robotics and Automation (ICRA). IEEE (2021). https:\/\/doi.org\/10.1109\/icra48506.2021.9561439","DOI":"10.1109\/icra48506.2021.9561439"},{"key":"21_CR11","doi-asserted-by":"publisher","first-page":"219","DOI":"10.4436\/JASS.95006","volume":"95","author":"M Lombard","year":"2017","unstructured":"Lombard, M., G\u00e4rdenfors, P.: Tracking the evolution of causal cognition in humans. J. Anthropol. Sci. 95, 219\u2013234 (2017). https:\/\/doi.org\/10.4436\/JASS.95006","journal-title":"J. Anthropol. Sci."},{"key":"21_CR12","doi-asserted-by":"publisher","unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization (2017). https:\/\/doi.org\/10.48550\/arXiv.1711.05101","DOI":"10.48550\/arXiv.1711.05101"},{"key":"21_CR13","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. NIPS\u201917, vol.\u00a030, p. 4768\u20134777 (2017)"},{"issue":"1","key":"21_CR14","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s10994-010-5202-y","volume":"81","author":"A Nouri","year":"2010","unstructured":"Nouri, A., Littman, M.L.: Dimension reduction and its application to model-based exploration in continuous spaces. Mach. Learn. 81(1), 85\u201398 (2010). https:\/\/doi.org\/10.1007\/s10994-010-5202-y","journal-title":"Mach. Learn."},{"key":"21_CR15","doi-asserted-by":"publisher","unstructured":"Pearl, J.: Causality: Models, Reasoning, and Inference. Cambridge University Press, New York, NY, 2 edn. (2009). https:\/\/doi.org\/10.1017\/cbo9780511803161","DOI":"10.1017\/cbo9780511803161"},{"key":"21_CR16","volume-title":"Elements of Causal Inference - Foundations and Learning Algorithms","author":"J Peters","year":"2017","unstructured":"Peters, J., Janzing, D., Bernard, S.: Elements of Causal Inference - Foundations and Learning Algorithms. MIT Press, Cambridge, MA, USA (2017)"},{"key":"21_CR17","doi-asserted-by":"publisher","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: \"Why Should I Trust You?\": explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144. ACM (2016). https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"key":"21_CR18","doi-asserted-by":"publisher","unstructured":"Sch\u00f6lkopf, B.: Causality for machine learning, pp. 765\u2013804. ACM, New York, NY, USA, 1 edn. (2022). https:\/\/doi.org\/10.1145\/3501714.3501755","DOI":"10.1145\/3501714.3501755"},{"issue":"3","key":"21_CR19","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s002210050738","volume":"126","author":"JP Scholz","year":"1999","unstructured":"Scholz, J.P., Sch\u00f6ner, G.: The uncontrolled manifold concept: identifying control variables for a functional task. Exp. Brain Res. 126(3), 289\u2013306 (1999). https:\/\/doi.org\/10.1007\/s002210050738","journal-title":"Exp. Brain Res."},{"key":"21_CR20","unstructured":"Shrikumar, A., Greenside, P., Kundaje, A.: Learning important features through propagating activation differences. In: Proceedings of the 34th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a070, pp. 3145\u20133153. PMLR (2017)"},{"key":"21_CR21","doi-asserted-by":"publisher","unstructured":"Vavre\u010dka, M., Sokovnin, N., Mejdrechov\u00e1, M., \u0160ejnov\u00e1, G.: mygym: modular toolkit for visuomotor robotic tasks. In: 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), pp. 279\u2013283. IEEE (2021). https:\/\/doi.org\/10.1109\/ictai52525.2021.00046","DOI":"10.1109\/ictai52525.2021.00046"},{"issue":"7\u20138","key":"21_CR22","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1016\/s0893-6080(98)00066-5","volume":"11","author":"DM Wolpert","year":"1998","unstructured":"Wolpert, D.M., Kawato, M.: Multiple paired forward and inverse models for motor control. Neural Netw. 11(7\u20138), 1317\u20131329 (1998). https:\/\/doi.org\/10.1016\/s0893-6080(98)00066-5","journal-title":"Neural Netw."},{"issue":"1","key":"21_CR23","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1093\/nsr\/nwx137","volume":"5","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Sch\u00f6lkopf, B., Spirtes, P., Glymour, C.: Learning causality and causality-related learning: some recent progress. Natl. Sci. Rev. 5(1), 26\u201329 (2017). https:\/\/doi.org\/10.1093\/nsr\/nwx137","journal-title":"Natl. Sci. Rev."},{"issue":"3","key":"21_CR24","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1016\/j.eng.2020.01.011","volume":"6","author":"Y Zhu","year":"2020","unstructured":"Zhu, Y., et al.: Dark, beyond deep: a paradigm shift to cognitive AI with humanlike common sense. Engineering 6(3), 310\u2013345 (2020). https:\/\/doi.org\/10.1016\/j.eng.2020.01.011","journal-title":"Engineering"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72359-9_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T12:36:51Z","timestamp":1726663011000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72359-9_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031723582","9783031723599"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72359-9_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"18 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lugano","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Switzerland","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":"33","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}