last modified: 10 Jun 2021
Much progress has been made in robotics through the introduction of machine learning, often leading to autonomous systems that are effective but opaque with inexplicable behaviours.
Many applications, however, require robots to explicitly capture knowledge and reason with it in order to achieve high-level cognitive skills. This special session is devoted to exploring the intersection of Knowledge Representation and Robotics.
Papers are solicited in all areas of this intersection. In particular, we welcome papers that extend knowledge representation techniques to cope with the challenges posed by interacting with the physical world, such as:
Robots are the archetypical integrated cognitive systems. Thus, we also welcome papers that address the integration of knowledge representation into whole robotic systems, such as:
Finally, we welcome papers that show concrete examples where real robotic systems benefit from knowledge representation, for instance in:
The Special Session on KR & Robotics will allow contributions of both regular papers (9 pages) and short papers (4 pages), excluding references, prepared and submitted according to the authors guidelines detailed on the submission page .
The special session emphasizes KR & Robotics, and welcomes contributions that extend the state of the art at the intersection of KR & Robotics. Therefore, KR-only or Robotics-only submissions will not be accepted for evaluation in this special session.
Submissions will be rigorously peer reviewed by PC members who are active in KR & Robotics. Submissions will be evaluated on the basis of the overall quality of their technical contribution, including criteria such as originality, soundness, relevance, significance, quality of presentation, and understanding of the state of the art.
Alessandro Saffiotti (University of Orebro, Sweden)
Mary-Anne Williams (University of New South Wales, Australia)
Copyright © 2020 Principles of Knowledge Representation and Reasoning Inc
no cookie stored | privacy policy | webmaster