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<span style="-webkit-font-kerning: none; color: rgb(26, 26, 26); -webkit-text-stroke-color: rgb(26, 26, 26);" class=""><b class="">Call for Papers for Frontiers Research Topic on "</b></span><span style="font-kerning: none" class=""><b class="">Lifelong Learning
and Long-Term Human-Robot Interaction</b></span><span style="-webkit-font-kerning: none; color: rgb(26, 26, 26); -webkit-text-stroke-color: rgb(26, 26, 26);" class=""><b class="">"</b></span></div>
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<span style="font-kerning: none" class=""><b class="">Deadlines:</b> Oct 16, 2020, abstracts; Feb 19, 2021 manuscripts</span></div>
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<span style="font-kerning: none; color: #1a1a1a; background-color: #ffffff" class=""><b class="">URL:</b> <a href="https://www.frontiersin.org/research-topics/14495/lifelong-learning-and-long-term-human-robot-interaction" class=""><span style="-webkit-font-kerning: none; color: rgb(0, 0, 233); background-color: transparent;" class="">https://www.frontiersin.org/research-topics/14495/lifelong-learning-and-long-term-human-robot-interaction</span></a></span></div>
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<span style="font-kerning: none" class=""><b class="">About this Research Topic</b></span></div>
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<span style="font-kerning: none" class="">Social robots should be able to operate in highly challenging environments populated with complex objects and in social settings involving humans, animals, and other robots. Despite these challenges, we expect these
robots to be mindful towards us while executing their tasks, demonstrating adaptive behaviors.</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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</span><span style="font-kerning: none" class="">Conventional machine learning approaches do not scale well with the dynamic nature of such real-world interactions as they require samples from stationary data distributions. The real-world is not stationary,
it changes continuously. In such contexts, training data and learning objectives may also change rapidly. Lifelong learning is able to address this problem by learning incrementally and facilitating the learning of new concepts, situations, and abilities.
Consider a robot that is vacuuming while a person is reading a newspaper. When given a negative feedback in this situation, the robot should be able to identify this as a new context, and thereon adapt its behaviors accordingly in similar spatial or social
contexts - e.g., when people are watching TV, the robot should be able to link this situation to the previously experienced one and avoid vacuuming.</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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</span><span style="font-kerning: none" class="">The Research Topic seeks answers to the following challenges:</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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<i class="">RC1: What can we learn from Social Sciences?</i><br class="">
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</span><span style="font-kerning: none" class="">Humans excel in developing their skills using new experiences, without suffering the adverse effects of catastrophic forgetting. Understanding the mechanisms enabling this crucial capability is one of the important
goals.</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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<i class="">RC2: What can we learn from Machine Learning?</i><br class="">
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</span><span style="font-kerning: none" class="">For an embodied agent, lifelong learning brings </span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><i class="">new perspectives
and addresses many critical issues while introducing other challenges</i></span><span style="font-kerning: none" class="">. Tackling this critical problem requires more established research agenda which can significantly benefit from the growing literature
of established methods in machine learning.</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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<i class="">RC3: What issues should be addressed while adopting lifelong learning methods for HRI and social robotics?</i><br class="">
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</span><span style="font-kerning: none" class="">Lifelong learning leads to new challenges for the robotics community, e.g.: What cues can be used for making decisions about a new experience from which a concept can be learned? (How can old knowledge/skills
be kept while learning new ones? How can seemingly different situations be represented so that they are considered similar? How can lifelong learning be integrated into a fully-fledged cognitive architecture?</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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<i class="">RC4: What other alternative approaches can we adopt to foster successful long-term HRI?</i><br class="">
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</span><span style="font-kerning: none" class="">For example, program repair and synthesis is a promising alternative adapting to user context in the long term.</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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</span><span style="font-kerning: none" class="">We invite regular papers or position papers from a wide range of theoretical, experimental, and methodological approaches, from traditional quantitative, qualitative and mixed methods, through to ethnomethodology
and new/emergent methods for studying </span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><i class="">long-term/lifelong and longitudinal human-robot interaction</i></span><span style="font-kerning: none" class="">.</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
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</span><span style="font-kerning: none" class="">Suggested topics include, but are not limited to:</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Lifelong personalization and/or adaptation</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Modelling user(s) and/or user behavior(s) in multi-session/long-term HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Modelling robot behavior in multi-session/long-term HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Modelling context in multi-session/long-term HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Agent/robot architectures for personalization / adaptation</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Lifelong (long-term) human-agent interactions</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Lifelong (long-term) multimodal interaction</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Lifelong (long-term) multi-user/multi-agent interaction</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Continual/lifelong machine learning</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Alternative approaches (e.g. interactive program repair)</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Development concerns, including deployment, scalability and complexity</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Tools and testbeds for evaluation of multi-session/long-term HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Methodological challenges for achieving successful long-term HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Data analysis and statistical techniques for long-term/lifelong HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Metrics for evaluating long-term/lifelong HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Deployed and/or emerging applications for long-term HRI</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● User studies</span><span style="font-stretch: normal; line-height: normal; font-family: "Helvetica Light"; -webkit-font-kerning: none;" class=""><br class="">
</span><span style="font-kerning: none" class="">● Philosophical, legal and ethical considerations</span></div>
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<span style="font-kerning: none; background-color: #ffffff" class=""><b class="">Submission Deadlines</b></span></div>
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<span style="background-color: #ffffff" class=""></span><span style="font-kerning: none; background-color: #ffffff" class="">16 October 2020, Abstract</span>
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<span style="font-kerning: none" class="">19 February 2021, Manuscript</span> </li><li style="margin: 0px; font-stretch: normal; font-size: 15px; line-height: normal; font-family: "Lucida Grande"; color: rgb(26, 26, 26); -webkit-text-stroke-width: initial; -webkit-text-stroke-color: rgb(26, 26, 26); min-height: 18px;" class="">
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Note: Submissions will be reviewed and processed as soon as they are submitted. <span style="font-kerning: none" class="">
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<span style="font-kerning: none; background-color: #ffffff" class=""><b class="">Topic Editors</b></span></div>
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<span style="background-color: #ffffff" class=""></span><span style="font-kerning: none; background-color: #ffffff" class="">Hatice Gunes, University of Cambridge, United Kingdom</span>
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<span style="background-color: #ffffff" class=""></span><span style="font-kerning: none; background-color: #ffffff" class="">Sinan Kalkan, Middle East Technical University, Turkey</span>
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<span style="font-kerning: none" class="">German I. Parisi, University of Hamburg, Germany</span>
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Iolanda Leite, KTH Royal Institute of Technology, Sweden<span style="font-kerning: none" class=""><br class="">
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<span style="font-kerning: none; background-color: #ffffff" class=""><b class="">More Information and Submission System</b></span></div>
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<span style="text-decoration: underline ; font-kerning: none" class=""><a href="https://www.frontiersin.org/research-topics/14495/lifelong-learning-and-long-term-human-robot-interaction" class="">https://www.frontiersin.org/research-topics/14495/lifelong-learning-and-long-term-human-robot-interaction</a></span></div>
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Iolanda Leite<br class="">
Associate Professor<br class="">
KTH Royal Institute of Technology<br class="">
School of Electrical Engineering and Computer Science<br class="">
Division of Robotics, Perception and Learning (RPL)<br class="">
<br class="">
Lindstedtsvägen 24, 4th floor, SE-100 44 Stockholm, Sweden<br class="">
<a href="https://iolandaleite.com" class="">https://iolandaleite.com</a></div>
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