Lifelong Learning and Personalization in Long-Term Human-Robot Interaction 2024

The complex and largely unstructured nature of real-world situations makes it difficult for conventional closed-world robot learning solutions to adapt to such interaction dynamics. These challenges become particularly pronounced in long-term interactions where robots need to go beyond their past learning to continuously evolve with changing environment settings and personalize towards individual user behaviors. In contrast, open-world learning embraces the complexity and unpredictability of the real world, enabling robots to be “lifelong learners” that continuously acquire new knowledge and navigate novel challenges, making them more context-aware while intuitively engaging the users. This fourth edition of the “Lifelong Learning and Personalization in Long-Term Human-Robot Interaction (LEAP-HRI)” workshop seeks to bring together interdisciplinary perspectives on real-world applications in human-robotinteraction (HRI), including education, rehabilitation, elderly care, service, and companion robotics. The primary objective is to explore the concept of lifelong robot learning and the ability to continually adapt to users, contexts and environments in long-term HRI. Theworkshop’s goal is to foster collaboration and understanding across diverse scientific communities. This will be achieved through a combination of invited keynote presentations and in-depth discussions facilitated by contributed talks, break-out session, and a debate centered around the workshop’s theme. Aligned with the theme of the HRI 2024 conference, “HRI in the real world”, our workshop adopts the theme of “open-world learning”. This encourages the exploration of HRI theories, methodologies, designs, and studies focused on lifelong learning and personalization to learn and adapt to new concepts, users, and tasks after deployment in real-world applications in HRI.