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Special Session on Cognitive Architectures for Personalized Assistive Robots
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Conference: 32nd IEEE International Conference on Robot and Human Interactive Communication (IEEE RO-MAN 2023)
Location: Paradise Hotel in Busan, South Korea
Date: August 28 to 31, 2023
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Important Dates
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Paper Submission Deadline: March 17, 2023 (AoE)
Notification of Acceptance: May 26, 2023
Final Paper Submission: June 30, 2023
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Aim and Scope
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Assistive robots are becoming an integral part of our daily lives in a variety of roles, such as caretakers, cleaning robots, home assistants, and autonomous vehicles. However, developing general-purpose assistive robots is challenging, as it requires cognitive architectures that integrate multiple knowledge sources and reasoning elements to perform necessary tasks in the real world. For example, consider a household assistive robot setting up a breakfast table. This task requires a cognitive architecture with integrated knowledge about household objects (e.g., cereal box), relations between different objects (e.g., cereal can be poured from cereal box into a bowl), relations between objects and household contexts (e.g., cereal box can be found in the kitchen), and a reasoning framework on how to use the learned knowledge to perform household tasks (e.g., setting up a table for breakfast requires a cereal box). Creating such integrated cognitive architectures may result in breakthroughs in artificial intelligence and assistive robotics.
Another challenge in developing cognitive architectures for assistive robots is that these architectures must be personalized to their users’ needs and environments. For example, for the household assistive robot, each user might have personal preferences about the kind of breakfast they like and might have a particular set of utensils in their home. In such cases, it is imperative for the assistive robot to learn the user preferences and the environment, through interaction with the user. Although extensive research has been conducted for developing cognitive architectures for social companion robots, home assistant robots, cognitive assistance robots, etc., many of these architectures are not developed to be personalized to their users. Therefore, in this special session, we focus on cognitive architectures for personalized assistive robots that could interact with and learn from their users to effectively assist the users with the necessary tasks. Our goal is to bring together researchers in multidisciplinary fields (e.g., Human-Robot Interaction (HRI), Artificial Intelligence (AI), Machine Learning (ML), and cognitive science) to present and discuss theoretical foundations, real-world applications, and HRI studies with assistive robots.
The primary list of topics of interest includes, but is not limited to:
- Cognitive architectures for robots
- Brain-inspired cognitive architectures
- Semantic reasoning frameworks
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Interactive task learning
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Interactive reinforcement learning
- Lifelong learning
- Embodied neural networks
- Human-robot teaching
- Long-term human-agent or multi-agent interactions
- Explainable and interpretable AI systems
- Robot control for assistive tasks
- Interactive and Intelligent interfaces for HRI
- Personalization for assistive robots
- Acceptability of robotic systems
- Human perceptions of assistive robots
- Healthcare robotics
- Home assistance robots
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Contributions
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Authors should submit their papers electronically in PDF format via the Papercept submission site. For the initial submission, a manuscript can be 6-8 pages including references. For the final submission, a manuscript should be 6 pages, With 2 additional pages allowed at an extra charge (TBA).
All papers are reviewed using a single-blind review process: authors declare their names and affiliations in the manuscript for the reviewers to see, but reviewers do not know each other's identities, nor do the authors receive information about who has reviewed their manuscript.
Authors should use the templates provided by the electronic submission system. The templates for US Letter format paper should be used. Please use the following templates:
Special Session Code: 77nn6
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Organizers
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• Ali Ayub, University of Waterloo, (a9ayub@uwaterloo.ca)
Regards,
Ali Ayub (on behalf of all the organizers)
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