Joint Workshop on Knowledge Diversity and Cognitive Aspects of KR (KoDis/CAKR)
Co-located with the 21st International Conference on Principles of Knowledge Representation and Reasoning (KR 2024) , November 2 -- 8, 2024 in Hanoi, Vietnam
This workshop is the joint continuation of the previous Workshop on Cognitive Aspects of KR (CAKR) and of the Workshop on Knowledge Diversity (KoDis). In view of partial overlap of topics and target audience, we organise the KoDis and CAKR workshops jointly this year.
The KoDis workshop intends to create a space of confluence and a forum for discussion for researchers interested in knowledge diversity in a wide sense, including diversity in terms of diverging perspectives, different beliefs, semantic heterogeneity and others. The importance of understanding and handling the different forms of diversity that manifest between knowledge formalisations (ontologies, knowledge bases, or knowledge graphs) is widely recognised and has led to the proposal of a variety of systems of representation, tackling overlapping aspects of this phenomenon.
Besides understanding the phenomenon and considering formal models for the representation of knowledge diversity, we are interested in the variety of reasoning problems that emerge in this context, including joint reasoning with possibly conflicting sources, interpreting knowledge from alternative viewpoints, consolidating the diversity as uncertainty, reasoning by means of argumentation between the sources and pursuing knowledge aggregations among others.
A non-exhaustive list of topics of interest for the KoDis workshop is given below.
The CAKR workshop deals with cognitively adequate approaches to knowledge representation and reasoning. Knowledge representation is a lively and well-established field of AI, where knowledge and belief are represented declaratively and suitable for machine processing. It is often claimed that this declarative nature makes knowledge representation cognitively more adequate than e.g. sub-symbolic approaches, such as machine learning. This cognitive adequacy has important ramifications for the explainability of approaches in knowledge representation, which on its turn is essential for the trustworthiness of these approaches. However, exactly how cognitive adequacy is ensured has been often left implicit, and connections with cognitive science and psychology are only recently being taken up.
The goal of the CAKR workshop is to bring together experts from fields including artificial intelligence, psychology, cognitive science and philosophy to discuss important questions related to cognitive aspects of knowledge representation, such as:
To encourage submissions of both mature and preliminary work, we invite both long and short papers, as well as reports on recently published papers in reputed venues. Submissions will be peer-reviewed to ensure quality and relevance to the workshop. The workshop will include time for audience discussion of the presentation allowing the group to have a better understanding of the issues, challenges, and ideas being presented. At least one author of each accepted paper will be required to attend the workshop to present the contribution.
Submissions should be of one of the following types:
We plan to publish informal proceedings in the CEUR Workshop Proceedings .
All dates are given Anywhere on Earth (AoE).