last modified: 20 Dec 2019
The key problems in robot capability yet to be solved are those of generalizable knowledge representation and of cognition based on that representation. How can computer memories represent knowledge to be retrieved by memory-based methods so that similar but not identical situations will call up the appropriate memories and thoughts?
As Gill Pratt suggests, knowledge representation is a key towards equipping robots with true cognition skills. In this special session, we invite contributions that extend the state of the art at the intersection of knowledge representation and robotics. We especially encourage contributions in integrated and interactive systems (e.g., systems that sense and reason), and contributions that include evaluations on physical robots (single or multiple).
Papers are solicited in all areas, including, but not limited to, one or more of the following:
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 Authors Guidelines for KR2020.
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.
Michael Beetz (University of Bremen, Germany) Friedrik Heintz (Linköping University, Sweden)