{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:51:21Z","timestamp":1742914281201,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030862299"},{"type":"electronic","value":"9783030862305"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-86230-5_32","type":"book-chapter","created":{"date-parts":[[2021,9,7]],"date-time":"2021-09-07T09:03:00Z","timestamp":1631005380000},"page":"405-417","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploiting Symmetry in Human Robot-Assisted Dressing Using Reinforcement Learning"],"prefix":"10.1007","author":[{"given":"Pedro","family":"Ildefonso","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pedro","family":"Rem\u00e9dios","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Silva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel","family":"Vasco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco S.","family":"Melo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana","family":"Paiva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuela","family":"Veloso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,3]]},"reference":[{"key":"32_CR1","unstructured":"Average life expectancy by country. https:\/\/www.worlddata.info\/life-expectancy.php#by-world"},{"key":"32_CR2","unstructured":"Barrett, S., Taylor, M., Stone, P.: Transfer learning for reinforcement learning on a physical robot. In: AAMAS Workshop on Adaptive Learning Agents (2010)"},{"issue":"1","key":"32_CR3","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2021","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S., Sheikh, Y.: OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43(1), 172\u2013186 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"32_CR4","unstructured":"Christiano, P., et al.: Transfer from simulation to real world through learning deep inverse dynamics model. CoRR abs\/1610.03518 (2016)"},{"key":"32_CR5","unstructured":"Gao, Y., Chang, H., Demiris, Y.: User modelling for personalised dressing assistance by humanoid robots. In: Proceedings of 2015 IEEE\/RSJ International Conference Intelligent Robots and Systems, pp. 1840\u20131845 (2015)"},{"issue":"3","key":"32_CR6","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1109\/TCDS.2018.2817283","volume":"11","author":"A Jevti\u0107","year":"2019","unstructured":"Jevti\u0107, A., et al.: Personalized robot assistant for support in dressing. IEEE Trans. Cognitive Developmental Syst. 11(3), 363\u2013374 (2019)","journal-title":"IEEE Trans. Cognitive Developmental Syst."},{"key":"32_CR7","doi-asserted-by":"crossref","unstructured":"Klee, S., Ferreira, B., Silva, R., Costeira, J., Melo, F., Veloso, M.: Personalized assistance for dressing users. In: Proceedings of 7th International Conference Social Robotics (2015)","DOI":"10.1007\/978-3-319-25554-5_36"},{"key":"32_CR8","doi-asserted-by":"crossref","unstructured":"Maeda, G., Ewerton, M., Lioutikov, R., Amor, H., Peters, J., Neumann, G.: Learning interaction for collaborative tasks with probabilistic movement primitives. In: Proceedings of the 2014 IEEE-RAS International Conference Humanoid Robots, pp. 527\u2013534 (2014)","DOI":"10.1109\/HUMANOIDS.2014.7041413"},{"key":"32_CR9","unstructured":"Mahler, J., Goldberg, K.: Learning deep policies for robot bin picking by simulating robust grasping sequences. In: Proceedings of 1st Annual Conference Robot Learning (2017)"},{"key":"32_CR10","doi-asserted-by":"crossref","unstructured":"Olson, E.: AprilTag: a robust and and flexible visual fiducial system. In: Proceedings of 2011 IEEE International Conference Robotics and Automation, pp. 3400\u20133407 (2011)","DOI":"10.1109\/ICRA.2011.5979561"},{"key":"32_CR11","unstructured":"Puterman, M.: Markov Decision Processes: Discrete Stochastic Dynamic Programming. John Wiley & Sons (2014)"},{"key":"32_CR12","unstructured":"Rahimi, A., Recht, B.: Weighted sums of random kitchen sinks: Replacing minimization with randomization in learning. In: Advances in Neural Information Processing Systems 22, pp. 1313\u20131320 (2009)"},{"issue":"4","key":"32_CR13","doi-asserted-by":"publisher","first-page":"1328","DOI":"10.1109\/TKDE.2019.2946162","volume":"33","author":"Y Roh","year":"2019","unstructured":"Roh, Y., Heo, G., Whang, S.: A survey on data collection for machine learning: a big data-AI integration perspective. IEEE Trans. Knowl. Data Eng. 33(4), 1328\u20131347 (2019)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"32_CR14","unstructured":"ce Rosenthal, S., Biswas, J., Veloso, M.: An effective personal mobile robot agent through symbiotic human-robot interaction. In: Proceedings of 9th International Conference Autonomous Agents and Multiagent Systems, pp. 915\u2013922 (2010)"},{"key":"32_CR15","unstructured":"Rusu, A., Ve\u010derik, M., Roth\u00f6rl, T., Heess, N., Pascanu, R., Hadsell, R.: Sim-to-real robot learning from pixels with progressive nets. In: Proceedings of 1st Annual Conference Robot Learning (2017)"},{"key":"32_CR16","doi-asserted-by":"crossref","unstructured":"Silva, R., Faria, M., Melo, F., Veloso, M.: Adaptive indirect control through communication in collaborative human-robot interaction. In: Proceedings of 2017 IEEE\/RSJ International Conference Intelligent Robots and Systems, pp. 3617\u20133622 (2017)","DOI":"10.1109\/IROS.2017.8206208"},{"key":"32_CR17","unstructured":"Silva, R., Melo, F., Veloso, M.: Adaptive symbiotic collaboration for targeted complex manipulation tasks. In: Proceedings of 22nd Eur. Conf. Artificial Intelligence (2016)"},{"key":"32_CR18","doi-asserted-by":"crossref","unstructured":"Sutton, R.: Integrated architectures for learning, planning, and reacting based on approximating dynamic programming. In: Proceedings of 7th International Conference Machine Learning, pp. 216\u2013224 (1990)","DOI":"10.1016\/B978-1-55860-141-3.50030-4"},{"key":"32_CR19","unstructured":"Sutton, R., Barto, A.: Reinforcement Learning: An Introduction. MIT Press (2018)"},{"key":"32_CR20","unstructured":"Veloso, M., Biswas, J., Coltin, B., Rosenthal, S.: CoBots: robust symbiotic autonomous mobile service robots. In: Proceedings of 24th International Joint Conference Artificial Intelligence, pp. 4423\u20134429 (2015)"},{"key":"32_CR21","unstructured":"Watkins, C.: Learning from delayed rewards. Ph.D. thesis, King\u2019s College, Cambridge University (1989)"}],"container-title":["Lecture Notes in Computer Science","Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86230-5_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,7]],"date-time":"2021-09-07T09:12:08Z","timestamp":1631005928000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86230-5_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030862299","9783030862305"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86230-5_32","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"3 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EPIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"EPIA Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"epia2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.appia.pt\/epia2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-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":"108","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":"62","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":"57% - 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":"3.47","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":"1.36","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)"}}]}}