{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T05:55:56Z","timestamp":1775109356436,"version":"3.50.1"},"publisher-location":"Cham","reference-count":39,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030620554","type":"print"},{"value":"9783030620561","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-62056-1_3","type":"book-chapter","created":{"date-parts":[[2020,11,7]],"date-time":"2020-11-07T06:02:42Z","timestamp":1604728962000},"page":"23-35","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Explainable Agency by Revealing Suboptimality in Child-Robot Learning Scenarios"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6826-370X","authenticated-orcid":false,"given":"Silvia","family":"Tulli","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5841-4263","authenticated-orcid":false,"given":"Marta","family":"Couto","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5761-4105","authenticated-orcid":false,"given":"Miguel","family":"Vasco","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7091-0104","authenticated-orcid":false,"given":"Elmira","family":"Yadollahi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5705-7372","authenticated-orcid":false,"given":"Francisco","family":"Melo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3998-5188","authenticated-orcid":false,"given":"Ana","family":"Paiva","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,6]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","first-page":"700","DOI":"10.3389\/fnhum.2014.00700","volume":"8","author":"T Lombrozo","year":"2014","unstructured":"Lombrozo, T., Gwynne, N.Z.: Explanation and inference: mechanistic and functional explanations guide property generalization. Front. Hum. Neurosci. 8, 700 (2014)","journal-title":"Front. Hum. Neurosci."},{"key":"3_CR2","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1146\/annurev.psych.57.102904.190100","volume":"57","author":"F Keil","year":"2006","unstructured":"Keil, F.: Explanation and understanding. Annu. Rev. Psychol. 57, 227\u201354 (2006)","journal-title":"Annu. Rev. Psychol."},{"key":"3_CR3","unstructured":"Anjomshoae, S., Najjar, A., Calvaresi, D., Fr\u00e4mling, K.: Explainable agents and robots: results from a systematic literature review. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, pp. 1078\u20131088 (2019)"},{"key":"3_CR4","unstructured":"Miller, T.: Explanation in artificial intelligence: insights from the social sciences, CoRR, abs\/1706.07269 (2017). http:\/\/arxiv.org\/abs\/1706.07269"},{"key":"3_CR5","unstructured":"Kambhampati, S.: Challenges of human-aware AI systems, ArXiv abs\/1910.07089 (2019)"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Chakraborti, T., Sreedharan, S., Zhang, Y., Kambhampati, S.: Plan explanations as model reconciliation: moving beyond explanation as soliloquy (2017)","DOI":"10.24963\/ijcai.2017\/23"},{"key":"3_CR7","unstructured":"Fox, M., Long, D., Magazzeni, D.: Explainable planning, arXiv preprint arXiv:1709.10256 (2017)"},{"key":"3_CR8","unstructured":"Miller, T.: Contrastive explanation: a structural-model approach, November 2018"},{"key":"3_CR9","unstructured":"Madumal, P., Miller, T., Sonenberg, L., Vetere, F.: Explainable reinforcement learning through a causal lens, ArXiv, abs\/1905.10958 (2019)"},{"key":"3_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1007\/BFb0095304","volume-title":"PRICAI\u201998: Topics in Artificial Intelligence","author":"A Kean","year":"1998","unstructured":"Kean, A.: A characterization of contrastive explanations computation. In: Lee, H.-Y., Motoda, H. (eds.) PRICAI 1998. LNCS, vol. 1531, pp. 599\u2013610. Springer, Heidelberg (1998). https:\/\/doi.org\/10.1007\/BFb0095304"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Hoffmann, J., Magazzeni, D.: Explainable AI planning (XAIP): overview and the case of contrastive explanation (extended abstract). In: Reasoning Web (2019)","DOI":"10.1007\/978-3-030-31423-1_9"},{"key":"3_CR12","unstructured":"Rathi, S.: Generating counterfactual and contrastive explanations using shap, ArXiv, abs\/1906.09293 (2019)"},{"key":"3_CR13","unstructured":"Borgo, R., Cashmore, M., Magazzeni, D.: Towards providing explanations for AI planner decisions (2018)"},{"key":"3_CR14","unstructured":"Cashmore, M., Collins, A., Krarup, B., Krivic, S., Magazzeni, D., Smith, D.: Towards explainable AI planning as a service, arXiv preprint arXiv:1908.05059 (2019)"},{"key":"3_CR15","unstructured":"Perera, V., Veloso, M.: Interpretability of a service robot: enabling user questions and checkable answers. In: GCAI (2018)"},{"key":"3_CR16","unstructured":"Krarup, B., Cashmore, M., Magazzeni, D., Miller, T.: Model-based contrastive explanations for explainable planning (2019)"},{"key":"3_CR17","doi-asserted-by":"crossref","unstructured":"Lindsay, A.: Towards exploiting generic problem structures in explanations for automated planning. In: Proceedings of the 10th International Conference on Knowledge Capture, pp. 235\u2013238 (2019)","DOI":"10.1145\/3360901.3364419"},{"key":"3_CR18","unstructured":"Sengupta, S., Chakraborti, T., Sreedharan, S., Vadlamudi, S.G., Kambhampati, S.: Radar - a proactive decision support system for human-in-the-loop planning. In AAAI Fall Symposia (2017)"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Topin, N., Veloso, M.: Generation of policy-level explanations for reinforcement learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 2514\u20132521 2019)","DOI":"10.1609\/aaai.v33i01.33012514"},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Ehsan, U., Tambwekar, P., Chan, L., Harrison, B., Riedl, M.O.: Automated rationale generation: a technique for explainable AI and its effects on human perceptions. In: Proceedings of the 24th International Conference on Intelligent User Interfaces, pp. 263\u2013274. ACM (2019)","DOI":"10.1145\/3301275.3302316"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"Wang, N., Pynadath, D.V., Hill, S.G.: Trust calibration within a human-robot team: comparing automatically generated explanations. In: 2016 11th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), pp. 109\u2013116, March 2016","DOI":"10.1109\/HRI.2016.7451741"},{"key":"3_CR22","unstructured":"Lemaignan, S., Dillenbourg, P.: Mutual modelling in robotics: inspirations for the next steps. In: ACM\/IEEE International Conference on Human-Robot Interaction, 2015, pp. 303\u2013310, March 2015"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Hayes, B., Shah, J.A.: Improving robot controller transparency through autonomous policy explanation. In: Proceedings of the 2017 ACM\/IEEE International Conference on Human-Robot Interaction, ser. HRI 2017, pp. 303\u2013312, New York. ACM (2017)","DOI":"10.1145\/2909824.3020233"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Tabrez, A., Hayes, B.: Improving human-robot interaction through explainable reinforcement learning. In: 2019 14th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), pp. 751\u2013753. IEEE (2019)","DOI":"10.1109\/HRI.2019.8673198"},{"key":"3_CR25","doi-asserted-by":"crossref","unstructured":"Akash, K., Polson, K., Reid, T., Jain, N.: Improving human-machine collaboration through transparency-based feedback - part I: human trust and workload model. In: 2nd IFAC Conference on Cyber-Physical and Human Systems CPHS 2018, IFAC-PapersOnLine, vol. 51, no. 34, pp. 315\u2013321 (2019)","DOI":"10.1016\/j.ifacol.2019.01.028"},{"key":"3_CR26","unstructured":"Hayes, B., Scassellati, B.: Challenges in shared-environment human-robot collaboration, January 2013"},{"key":"3_CR27","doi-asserted-by":"crossref","unstructured":"Langley, P., Meadows, B., Sridharan, M., Choi, D.: Explainable agency for intelligent autonomous systems. In: Twenty-Ninth IAAI Conference (2017)","DOI":"10.1609\/aaai.v31i2.19108"},{"key":"3_CR28","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1055\/s-0039-1677911","volume":"28","author":"S Montani","year":"2019","unstructured":"Montani, S., Striani, M.: Artificial intelligence in clinical decision support : a focused literature survey. Yearbook Med. Inf. 28, 120\u2013127 (2019)","journal-title":"Yearbook Med. Inf."},{"key":"3_CR29","unstructured":"Holstein, K.: Towards teacher-AI hybrid systems. In: Companion Proceedings of the Eigth International Conference on Learning Analytics and Knowledge (2018)"},{"key":"3_CR30","doi-asserted-by":"crossref","unstructured":"Tabrez, A., Agrawal, S., Hayes, B.: Explanation-based reward coaching to improve human performance via reinforcement learning. In: 2019 14th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), pp. 249\u2013257, March 2019","DOI":"10.1109\/HRI.2019.8673104"},{"key":"3_CR31","doi-asserted-by":"crossref","unstructured":"Kaptein, F., Broekens, J., Hindriks, K., Neerincx, M.: Personalised self-explanation by robots: the role of goals versus beliefs in robot-action explanation for children and adults. In: 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) 2017. pp. 676\u2013682. IEEE (2017)","DOI":"10.1109\/ROMAN.2017.8172376"},{"key":"3_CR32","doi-asserted-by":"crossref","unstructured":"Hitron, T., Orlev, Y., Wald, I., Shamir, A., Erel, H., Zuckerman, O.: Can children understand machine learning concepts? the effect of uncovering black boxes. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1\u201311 (2019)","DOI":"10.1145\/3290605.3300645"},{"key":"3_CR33","volume-title":"Artificial Intelligence: A Modern Approach","author":"S Russell","year":"2009","unstructured":"Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn. Prentice Hall Press, Upper Saddle River (2009)","edition":"3"},{"issue":"2","key":"3_CR34","doi-asserted-by":"publisher","first-page":"263","DOI":"10.2307\/1914185","volume":"47","author":"D Kahneman","year":"1979","unstructured":"Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47(2), 263\u2013291 (1979)","journal-title":"Econometrica"},{"issue":"1","key":"3_CR35","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1007\/s12369-008-0001-3","volume":"1","author":"C Bartneck","year":"2009","unstructured":"Bartneck, C., Kuli\u0107, D., Croft, E., Zoghbi, S.: Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. Soc. Robot. 1(1), 71\u201381 (2009)","journal-title":"Int. J. Soc. Robot."},{"key":"3_CR36","doi-asserted-by":"crossref","unstructured":"Bandura, A., Freeman, W., Lightsey, R.: Self-efficacy: the exercise of control (1999)","DOI":"10.1891\/0889-8391.13.2.158"},{"key":"3_CR37","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1027\/\/1015-5759.17.2.87","volume":"17","author":"C Pastorelli","year":"2001","unstructured":"Pastorelli, C., Caprara, G., Barbaranelli, C., Rola, J., R\u00f3zsa, S., Bandura, A.: The structure of children\u2019s perceived self-efficacy: a cross-national study. Eur. J. Psychol. Assess. 17, 87\u201397 (2001)","journal-title":"Eur. J. Psychol. Assess."},{"key":"3_CR38","unstructured":"Conati, C., Porayska-Pomsta, K., Mavrikis, M.: AI in education needs interpretable machine learning: lessons from open learner modelling (2018)"},{"key":"3_CR39","doi-asserted-by":"crossref","unstructured":"Chao, C., Cakmak, M., Thomaz, A.L.: Transparent active learning for robots. In: 2010 5th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), pp. 317\u2013324, March 2010","DOI":"10.1109\/HRI.2010.5453178"}],"container-title":["Lecture Notes in Computer Science","Social Robotics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-62056-1_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,27]],"date-time":"2022-11-27T05:10:06Z","timestamp":1669525806000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-62056-1_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030620554","9783030620561"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-62056-1_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"6 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Social Robotics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Golden, CO","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socrob2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.psu.edu\/icsr2020\/","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":"OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"101","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":"57","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":"56% - 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":"3","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":"2","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}