Relational Approaches to Knowledge Representation and Learning Workshop at the 32nd Annual Conference on Artificial Intelligence (KI-2009) September 15-18, 2009, Paderborn, Germany Organized by the FG Wissensrepräsentation und Schließen of the GI
[ Call for Papers ] [ Committee ] [ Dates ] [ Submission ] [ Program ] [ Local Information ]

Aims and Scope

Knowledge representation encompasses a variety of methods and formalisms to encode and process all types of knowledge, belief, and information. It provides the theoretical foundation for rational and intelligent behaviour in real environments, focusing on topics like default logics and uncertain reasoning, belief change, ontologies, and argumentation, among many others. Moreover, in a thematical respect, knowledge representation is closely related to the areas of machine learning and knowledge discovery the methods of which allow the acquisition of useful information to build up knowledge bases.

Knowledge representation has made substantial progress over the last decade by devising sophisticated methods for inference and reasoning. Nevertheless, the connection to learning still holds undeveloped potential in methodological and technical respects which might be crucial for practical applications. Furthermore, the handling of relational information, i.e. the explicit representation of knowledge about objects and its linking to knowledge about classes, is still a challenge for many subareas of knowledge representation. Ontologies, logic programming and probabilistic relational models are just some important examples of areas of research that address both of these points.

The aim of this workshop, organized by the GI-Fachgrupppe "Wissensrepräsentation und Schließen" is to strengthen the connection between knowledge representation and learning by focusing on relational and first-order approaches to all areas of knowledge representation and learning, in particular:

• Default and conditional logics
• Logic programming
• Uncertain reasoning
• Nonmonotonic and nonclassical logics
• Belief revision
• Probabilistic networks
• Inference processes
• Machine learning
• Data mining
• Knowledge discovery
• Ontologies
• Agent systems
• Applications

Publication

The proceedings will be published as a technical report that will be available at the workshop (now available: PDF, BibTeX). It is planned to publish a selection of extended papers after a post-workshop reviewing process in a special issue of the Logic Journal of the IGPL.

Workshop Organizers and Co-Chairs

Program Committee

Important Dates

Submission Details

Papers should be formated according to the Springer LNCS guidelines. The length of each paper should not exceed 15 pages. All papers must be written in English and submitted in PDF format. Submissions should be sent in electronic form to both workshop chairs (gabriele.kern-isberner@cs.uni-dortmund.de, christoph.beierle@fernuni-hagen.de).

Local Information

Local information can be found on the web pages of the KI-2009 conference.

Last modified 2009-09-23