{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T09:36:17Z","timestamp":1771666577362,"version":"3.50.1"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030937577","type":"print"},{"value":"9783030937584","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-93758-4_24","type":"book-chapter","created":{"date-parts":[[2022,1,6]],"date-time":"2022-01-06T18:05:41Z","timestamp":1641492341000},"page":"228-238","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Causal Generalization in\u00a0Autonomous Learning Controllers"],"prefix":"10.1007","author":[{"given":"Arash","family":"Sheikhlar","sequence":"first","affiliation":[]},{"given":"Leonard M.","family":"Eberding","sequence":"additional","affiliation":[]},{"given":"Kristinn R.","family":"Th\u00f3risson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,6]]},"reference":[{"key":"24_CR1","unstructured":"Baumann, D., Solowjow, F., Johansson, K.H., Trimpe, S.: Identifying causal structure in dynamical systems. arXiv preprint arXiv:2006.03906 (2020)"},{"key":"24_CR2","unstructured":"Bouvier, V., Very, P., Hudelot, C., Chastagnol, C.: Hidden covariate shift: a minimal assumption for domain adaptation. Technical report, arXiv preprint arXiv:1907.12299 (2019)"},{"key":"24_CR3","doi-asserted-by":"crossref","unstructured":"Drescher, G.L.: Made-Up Minds: A Constructivist Approach to Artificial Intelligence. MIT Press (1991)","DOI":"10.7551\/mitpress\/4378.001.0001"},{"key":"24_CR4","doi-asserted-by":"publisher","first-page":"4684","DOI":"10.1109\/TITS.2020.2990598","volume":"22","author":"Z Ke","year":"2020","unstructured":"Ke, Z., Li, Z., Cao, Z., Liu, P.: Enhancing transferability of deep reinforcement learning-based variable speed limit control using transfer learning. IEEE Trans. Intell. Transp. Syst. 22, 4684\u20134695 (2020)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"24_CR5","unstructured":"Nivel, E., et al.: Bounded recursive self-improvement. arXiv preprint arXiv:1312.6764 (2013)"},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"Pearl, J.: Causality, pp. 22\u201324. Cambridge University Press (2009)","DOI":"10.1017\/CBO9780511803161"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Pearl, J.: Theoretical impediments to machine learning with seven sparks from the causal revolution. arXiv preprint arXiv:1801.04016 (2018)","DOI":"10.1145\/3159652.3176182"},{"key":"24_CR8","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1111\/rssb.12167","volume":"78","author":"J Peters","year":"2016","unstructured":"Peters, J., B\u00fchlmann, P., Meinshausen, N.: Causal inference by using invariant prediction: identification and confidence intervals. J. Roy. Stat. Soc. Ser. B (Stat. Methodol.) 78, 947\u20131012 (2016)","journal-title":"J. Roy. Stat. Soc. Ser. B (Stat. Methodol.)"},{"key":"24_CR9","unstructured":"Peters, J., Janzing, D., Sch\u00f6lkopf, B.: Elements of Causal Inference: Foundations and Learning Algorithms, pp. 15\u201326, 88. The MIT Press (2017)"},{"key":"24_CR10","unstructured":"Piaget, J., Piercy, M., Berlyne, D.: The Psychology of Intelligence (1951)"},{"issue":"1","key":"24_CR11","first-page":"1309","volume":"19","author":"M Rojas-Carulla","year":"2018","unstructured":"Rojas-Carulla, M., Sch\u00f6lkopf, B., Turner, R., Peters, J.: Invariant models for causal transfer learning. Int. J. Biostat. 19(1), 1309\u20131342 (2018)","journal-title":"Int. J. Biostat."},{"key":"24_CR12","unstructured":"Shajarisales, N., Janzing, D., Sch\u00f6lkopf, B., Besserve, M.: Telling cause from effect in deterministic linear dynamical systems. In: International Conference on Machine Learning, pp. 285\u2013294. PMLR (2015)"},{"key":"24_CR13","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1007\/978-3-030-52152-3_32","volume-title":"Artificial General Intelligence","author":"A Sheikhlar","year":"2020","unstructured":"Sheikhlar, A., Th\u00f3risson, K.R., Eberding, L.M.: Autonomous cumulative transfer learning. In: Goertzel, B., Panov, A.I., Potapov, A., Yampolskiy, R. (eds.) AGI 2020. LNCS (LNAI), vol. 12177, pp. 306\u2013316. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-52152-3_32"},{"key":"24_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1007\/978-3-030-01424-7_27","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2018","author":"C Tan","year":"2018","unstructured":"Tan, C., Sun, F., Kong, T., Zhang, W., Yang, C., Liu, C.: A survey on deep transfer learning. In: K\u016frkov\u00e1, V., Manolopoulos, Y., Hammer, B., Iliadis, L., Maglogiannis, I. (eds.) ICANN 2018. LNCS, vol. 11141, pp. 270\u2013279. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01424-7_27"},{"issue":"7","key":"24_CR15","first-page":"1633","volume":"10","author":"ME Taylor","year":"2009","unstructured":"Taylor, M.E., Stone, P.: Transfer learning for reinforcement learning domains: a survey. J. Mach. Learn. Res. 10(7), 1633\u20131685 (2009)","journal-title":"J. Mach. Learn. Res."},{"key":"24_CR16","doi-asserted-by":"publisher","unstructured":"Th\u00f3risson, K.R.: A new constructivist AI: from manual methods to self-constructive systems. In: Wang, P., Goertzel, B. (eds.) Theoretical Foundations of Artificial General Intelligence. Atlantis Thinking Machines, vol. 4. Atlantis Press, Paris (2012). https:\/\/doi.org\/10.2991\/978-94-91216-62-6_9","DOI":"10.2991\/978-94-91216-62-6_9"},{"key":"24_CR17","first-page":"32","volume":"131","author":"KR Th\u00f3risson","year":"2020","unstructured":"Th\u00f3risson, K.R.: Seed-programmed autonomous general learning. Proc. Mach. Learn. Res. 131, 32\u201370 (2020)","journal-title":"Proc. Mach. Learn. Res."},{"key":"24_CR18","doi-asserted-by":"crossref","unstructured":"Th\u00f3risson, K.R., Bieger, J., Li, X., Wang, P.: Cumulative learning. In: Proceedings of the 12th International Conference on Artificial General Intelligence, pp. 198\u2013208 (2019)","DOI":"10.1007\/978-3-030-27005-6_20"},{"key":"24_CR19","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/978-3-319-97676-1_22","volume-title":"Artificial General Intelligence","author":"KR Th\u00f3risson","year":"2018","unstructured":"Th\u00f3risson, K.R., Talbot, A.: Cumulative learning with causal-relational models. In: Ikl\u00e9, M., Franz, A., Rzepka, R., Goertzel, B. (eds.) AGI 2018. LNCS (LNAI), vol. 10999, pp. 227\u2013237. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-97676-1_22"},{"key":"24_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/1-4020-5045-3","volume-title":"Rigid Flexibility: The Logic of Intelligence","author":"P Wang","year":"2006","unstructured":"Wang, P.: Rigid Flexibility: The Logic of Intelligence. Springer, Dordrecht (2006). https:\/\/doi.org\/10.1007\/1-4020-5045-3"}],"container-title":["Lecture Notes in Computer Science","Artificial General Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-93758-4_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T20:45:19Z","timestamp":1726433119000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-93758-4_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030937577","9783030937584"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-93758-4_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"6 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial General Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"San Francisco, CA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","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":"15 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"agi2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/agi-conf.org\/2021\/","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 (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":"50","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":"36","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":"72% - 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":"2.6","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":"3.8","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}