Scope & Description
Knowledge representation is a lively and well-established field of AI, where knowledge and belief is 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 have only recently been taken up.
The goal of this 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:
- How can we study the cognitive adequacy of approaches in AI?
- Are declarative approaches cognitively more adequate than other approaches in AI?
- What is the connection between cognitive adequacy and explanatory potential?
- How to develop benchmarks for studying cognitive aspects of AI?
- Which results from psychology are relevant for AI?
- What is the role of the normative-descriptive distinction in current developments in AI?
Keynote Talk
The keynote talk will be given by Claudia Schon (Hochschule Trier, Germany).
Towards Modeling Aspects of Human Reasoning.
Abstract:
Unlike automated reasoning, human reasoning does not adhere to logical rules exclusively. This is also reflected in the observation of Kahneman (and others) that the human mind seems to be based on two integrated systems: a System 1 that works quickly and unconsciously, and a System 2 that works slowly and calculates logically. System 1 embodies intuitions and fast reactions to sensory signals, while System 2 represents deliberate thinking and abstract problem solving.
Therefore, if we want to model aspects of human reasoning, a combination of statistical procedures and logical reasoning is promising.
The talk will present different ways to incorporate statistical methods into the automated reasoning process together with lessons learnt from this field.
Schedule
- 14:15-14:30 Opening
- 14:30-15:30 Keynote talk, Claudia Schon.
- 15:30-16:00 Unifying Abduction and Deduction through Argumentation, Antonis Kakas and Emmanuelle Dietz.
- 16:00-16:30 Coffee break
- 16:30-17:00 On the Cognitive Adequacy of Situation Calculus-Based Communicative Multiagent Systems, Maryam Rostamigiv and Shakil Khan.
- 17:00-17:30 Cognitively adequate complexity of reasoning in a description logic: extended abstract, Jelle Tjeerd Fokkens and Fredrik Engström.
- 17:30-18:00 On the Suitability of Inconsistency Measures, Carl Corea.
Online talk: recording available here.
KR 2023 Workshop
This workshop is part of the workshop programme of the 20th International Conference on Principles of Knowledge Representation and Reasoning (KR2023).CAKR 2022
This is the second edition of the CAKR-workshop. The website of the first edition can be found here: http://cakr22.krportal.org.Important Dates
June 7, 2023: Paper Due DateJuly 4, 2023: Notification of Paper AcceptanceJuly 22, 2023: Camera-ready papers due- September 4, 2023: Workshop (afternoon)
Organizing Committee
- Jesse Heyninck Open Universiteit, the Netherlands and University of Cape Town, South-Africa
- Tommie Meyer University of Cape Town and CAIR, South-Africa
- Clayton Baker University of Cape Town and CAIR, South-Africa
Support
