Call for Papers
Abstraction is a process that is exploited in human reasoning and understanding. Although the word itself comes from the meaning of "to draw away", there is no precise definition that is able to cover all the meanings that it gains depending on its utilisation. Various meanings of abstraction are interpreted in different disciplines such as Philosophy, Cognitive Science, Biomimetics, Mathematics and AI, with the shared consensus of the aim to distil the essential.
From the early days of AI research, including in the work of Alan Turing, such abstraction learning has been seen as a crucial heuristic for problem-solving. First, the problem is solved in a relaxed or reduced space, and then the abstract solution is used to guide the search for a solution in the original space. Since the success in solving a problem relies on how "good" the abstraction is, theoretical approaches for defining abstractions with desired properties have been and continue to be investigated while adhering to certain principles of simplification and/or generalization. Abstraction is also being used as a representation technique. Having different layers of representation that enable reasoning at a high level and refining to more low-level details only when necessary, e.g., in Robotics, allows one to determine the focus points of the problem. While usually the representation decisions are left to the experts, there are also methods, e.g. in Model Checking, to automatically find abstractions that allow one to check desired properties of the system at the abstract level. More recently, abstraction is becoming an essential technique for AI systems to present a “model of self”, overviewing their complex structures via showing the key elements making it easier for humans to understand their decision-making.
This workshop aims to bring together researchers from different sub-areas of KR and related communities who work on different aspects of abstraction in their respective areas, with the goal of exchanging theories and methods.
The following lists topics (but is not limited to these):
- Formation of concepts
- Symbol learning
- Inductive reasoning
- Abstraction and analogical reasoning
- Abstraction and generalization as operations
- The role of abstraction in knowledge
- Formal logical and philosophical foundations of abstraction
- Abstraction in ontological and conceptual modelling
- Systems which employ different levels of granularity
- Forgetting and marginalization
- Human-inspired theories of perception
- Application of abstraction in verification and software engineering
Submission
We invite short (6 pages) and long papers (13 pages) of unpublished work, or extended abstracts (2 pages) of already published works or works in progress. Reviewing will be single-blind, but anonymous submissions are possible.
- All submissions should be formatted in CEUR style (one-column style) without enabled header and footer. The author kit can be found at http://ceur-ws.org/Vol-XXX/CEURART.zip. Papers must be submitted in PDF only and should include an statement regarding usage of AI (see CEUR AI policy). For the camera-ready versions, one must also provide the LaTeX sources.
- Link the submission site will be added soon here.
Following the workshop, there will be an open call for inclusion in a special issue of the German Journal of Artificial Intelligence (KI).