We are announcing the second edition of the Actionable Knowledge Representation and Reasoning for Robots (AKR3) workshop, co-located with the International Semantic Web Conference (ISWC). The workshop is dedicated to Knowledge Representation and Reasoning (KRR) in the area of cognitive robotics, with the focus on acquiring knowledge from varying sources, knowledge engineering for applications, and making it actionable for robots. By bringing together different communities across the world that are currently specialized in KRR and robotics, we aim to increase collaboration and accelerate advancements in the field.
Given the availability of a plethora of sources and datasets for common sense knowledge on the Web, recent advances in language modelling as well as strides in learning through human-robot interaction, it is a timely research question to investigate which methods and approaches can enable robots to take advantage of existing knowledge to reason on how to perform tasks in the real world. The main issue to be addressed in particular is how to allow robots to perform tasks flexibly and adaptively, gracefully handling contextually determined variance in task execution. We expect this line of research to contribute to better generalizability and robustness of robots performing tasks in everyday environments.
For instance, household robots are still not able to autonomously prepare meals, set or clean the table or do other chores besides vacuum cleaning. Much of the knowledge needed to refine vague task instructions and transfer them to new task variations is contained in instruction websites like WikiHow, encyclopedic web sites like Wikipedia, and many other web-based information sources. We argue that such knowledge can be used to teach robots to perform new task variations.
Submission Guidelines
All papers must represent original work not submitted or published already at another workshop or conference. Submissions must adhere to the CEURART template. Please use the latest version of the template in single-column format to prepare your submissions in the following formats:
- Full papers: Up to 10 pages (excluding references) describing novel and substantial work including an evaluation / validation of the proposed approach
- Short papers: Up to 6 pages (excluding references) describing preliminary work or early results
- Position papers: Up to 6 pages (excluding references) describing insights towards new or emerging areas, innovative or risky approaches, or emerging applications that will require extensions to the state of the art.
Submissions for review must be in PDF format. They must be self-contained and written in English. Submissions that do not follow these guidelines will be rejected without review. The revieweing process is single-blind.
Please submit your paper using EasyChair: https://easychair.org/my/conference?conf=akr2025
List of Topics
- Knowledge Representation for cognitive robotics: The importance of linking object to action and environment information
- Knowledge-Enhanced Robotics: Integrating Knowledge Graphs and Question Answering for Enhanced Robot Capabilities
- Approaches to leverage common sense knowledge from varying sources (e.g. Web, LLMs, Interaction)
- Linking common sense knowledge to perception and execution
- Multi-modal AI Reasoning for Robotics: Multi-modal robot reasoning integrates diverse information for environmental understanding and interaction
- Translation of task requests to body movements and parameterization of such body movements with knowledge
- Novel formalisms and approaches to represent and encode knowledge for robots
- Novel cognitive architectures and paradigms supporting reasoning with Web knowledge
- Use of large language models and prompting to infer action-relevant knowledge
- Natural language processing applied to common sense knowledge extraction from unstructured sources
Publication
The accepted papers will be published on CEUR Workshop Proceedings (CEUR-WS.org) either as a standalone volume or in companion proceedings of ISWC 2025.
Contact
All questions about submissions should be emailed to Jan-Philipp Töberg at jtoeberg (at) techfak (dot) uni-bielefeld (dot) de