Workshops and Tutorials

List of Workshops

5th Workshop on Explainable Logic-Based Knowledge Representation (XLoKR 2024)
Nico Potyka, Franz Baader, Bart Bogaerts, Joerg Hoffmann, Thomas Lukasiewicz, Francesca Toni

The XLoKR workshop aims to bring together researchers interested in applying KR methods toexplainable AI. We encourage submissions of both novel ideas for discussion with the community and previously published ideas to increase their visibility.

1st International Workshop on Next-Generation Language Models for Knowledge Representation and Reasoning (NeLaMKRR 2024)
Ha Thanh Nguyen, Randy Goebel, Francesca Toni, Ken Satoh, Kostas Stathis

The aim of this workshop is to bring together researchers and practitioners working on the intersections of language models, knowledge representation, and reasoning, particularly, but not exclusively, in medical, law, and science domains. We encourage submissions that discuss novel techniques, approaches, and innovative ideas related to this topic.

International Workshop on Logical Aspects in Multi-Agent Systems and Strategic Reasoning (LAMAS&SR 2024)
Munyque Mittelmann, Aniello Murano, Angelo Ferrando

Logics and strategic reasoning play a central role in multi-agent systems. Logics can be used, for instance, to express the agents' abilities, knowledge, and objectives. Strategic reasoning refers to algorithmic methods that allow for developing good behaviour for the agents of the system. At the intersection, we find logics that can express the existence of strategies or equilibria, and can be used to reason about them. The LAMAS&SR workshop merges two international workshops: LAMAS (Logical Aspects of Multi-Agent Systems), which focuses on all kinds of logical aspects of multi-agent systems from the perspectives of artificial intelligence, computer science, and game theory, and SR (Strategic Reasoning), devoted to all aspects of strategic reasoning in formal methods and AI.

1st Workshop on Symbolic and Neuro-Symbolic Architectures for Intelligent Robotics Technology (SYNERGY)
Francesco Fabiano , Marcello Balduccini

SYNERGY aims at fostering in-depth discussions on Knowledge Representation (KR) and neuro-symbolic architectures with the goal of advancing intelligent robotics to new levels of sophistication. Integrating robust KR-based methodologies into robot-centric architectures holds significant promise for enhancing the intelligence of robotic systems. However, the development of such architectures is complex, typically involving diverse components each with unique challenges. Effective coordination among these components is essential, demanding well-defined yet flexible architectures. SYNERGY offers a platform for experts across these domains to share their research and experiences, focusing on the challenges encountered and potential solutions. While the workshop centers on KR-based architectures, we also invite submissions related to ML and LLMs, provided they clearly demonstrate relevance and significance to KR and neuro-symbolic architectures within the context of intelligent robotics.

Joint Workshop on Knowledge Diversity and Cognitive Aspects of KR (KoDis/CAKR 2024)
Lucia Gomez, Jonas Philipp Haldimann, Jesse Heyninck, Srdjan Vesic

This workshop is the joint continuation of the previous Workshop on Cognitive Aspects of KR (CAKR) and of the Workshop on Knowledge Diversity (KoDis). 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. 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. The CAKR workshop deals with cognitively adequate approaches to knowledge representation and reasoning. In knowledge representation, knowledge and belief are represented declaratively and intended for machine processing. It is often claimed that this declarative nature makes knowledge representation cognitively more adequate than e.g. sub-symbolic 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.

List of Tutorials

An introduction to approximation fixpoint theory
Jesse Heyninck, Hannes Strass

Large Language Models are Human-like Annotators
Manish Gupta, Mounika Marreddy, Subba Reddy Oota, Lucie Flek

Argumentation and Machine Learning
Antonio Rago, Kristijonas Cyras

Probing Machine Learning Models in Angluin's Style tutorial
Ana Ozaki

Fundamental Problems in Statistical Relational AI
Sagar Malhotra

Formal Aspects of Strategic Reasoning in Multi-Agent Systems
Munyque Mittelmann, Aniello Murano

Cogent: a Neuro-Symbolic Platform for KR&R in Natural Language
Marcello Balduccini

Iterated Belief Change
Richard Booth, Jake Chandler

Co-Located Workshops

22nd International Workshop on Nonmonotonic Reasoning (NMR 2024)