CALM 2024: Causality, Agents and Large Models 2024 Kyoto University Clock Tower Kyoto, Japan, November 18-19, 2024

Conference website	https://www.ciad-lab.fr/prima-causal-ai-workshop/
Submission link	https://easychair.org/conferences/?conf=calm2024
Submission deadline	September 26, 2024
Notification of acceptance	October 5, 2024

Workshop Introduction

Causality, Agents and Large Models (CALM) represent three rapidly-growing fields within artificial intelligence research. This workshop aims to bridge the gap between these disciplines by investigating how causality can be integrated in AI systems, while providing a forum for researchers to discuss theoretical foundations, practical applications, and future directions at the intersection of causal AI, Large Models and Multi-Agent Systems (MAS).

Workshop goals:

• Explore the role of causal reasoning in enhancing decision-making, coordination, and adaptation in multi-agent systems. 
• Discuss technical challenges and opportunities for integrating causal AI techniques with Large Models and MAS frameworks.
• Foster interdisciplinary collaboration between researchers in the fields of causal reasoning, Pre-trained Large Models, and MAS.
• Identify promising directions for future research and development in this emerging area.

Submission Guidelines

Submissions will be reviewed by at least three members of the program committee, who are experts in the field. The acceptance of the submitted papers will depend on their quality, relevance, and originality. 

Participants are therefore invited to submit the following two types of papers:

• Long papers: up to 16 pages in length (incl. references)
• Short papers: up to 5 pages in length (incl. references)

Papers must be edited using the LNCS format (applying the LNCS post-proceedings template) and have to be submitted electronically as PDF files via the EasyChair submission page:  https://easychair.org/my/conference?conf=calm2024

All papers will be subject to double-blind review.

Important Dates

• Submission deadline: September 26th October 12th (extended), 2024
• Notification: October 05thOctober 24th, 2024
• Final date for camera-ready copy: TBD
• Workshop: November 18-19, 2024

List of Topics

• Theoretical foundations of causal reasoning in Multi-Agent Systems (MAS)
• Causal reasoning capabilities in Large Models (e.g., Large Language Models, LLMs)
• Applications of causal AI techniques in agent-based modeling and simulation
• Causal inference in complex and dynamic multi-agent environments
• Mechanistic Interpretability of Causality in Large Language Models
• Integration of causal reasoning with decision-making and planning in MAS
• Learning causal models from observational and interventional data in MAS
• Causal reasoning for coordination, cooperation, and communication among agents
• Challenges and opportunities for incorporating causal AI into MAS frameworks
• Case studies and empirical evaluations of causal AI approaches in agents
• Generative AI as preprocessing for MAS
• Exploring causality with deep generative models
• Digital twins and simulators for interpretable synthetic data generation
• Graph neural network causal learning
• Causal reinforcement learning
• Interpretable/Explainable root cause analysis methods
• Explainable AI with active inference techniques
• Logic and argumentation-based approaches to causal reasoning

Committees

Workshop Chairs

• Dr. Yazan Mualla (Belfort-Montbeliard University of Technology, France). yazan.mualla[at]utbm.fr
• Dr. Liuwen Yu (University of Luxembourg, Luxembourg). liuwen.yu[at]uni.lu
• Dr. Davide Liga (University of Luxembourg, Luxembourg). davide.liga[at]uni.lu 
• Dr. Igor Tchappi (University of Luxembourg, Luxembourg). igor.tchappi[at]uni.lu
• Dr. Réka Markovich (University of Luxembourg, Luxembourg). reka.markovich[at]uni.lu

Advisory Board

• Prof. Dr. Stéphane Galland (Belfort-Montbeliard University of Technology, France)
• Prof. Dr. Abdeljalil Abbas-Turki (Belfort-Montbeliard University of Technology, France)

Program Committee

• Ilaria Amantea, University of Turin

• Sukriti Bhattacharya, Luxembourg Institute of Science and Technology

• Diderot Cidjeu, University of Ngaoundere

• Alaa Daoud, INSA Rouen Normandie

• Stéphane Galland, Université de Technologie de Belfort Montbéliard

• Eskandar Kouicem, Ingenico Terminals

• Salima Lamsiyah, University of Luxembourg

• Beishui Liao, Zhejiang University

• Alexandre Lombard, Université de Technologie de Belfort-Montbéliard

• Giuseppe Pisano, Alma Mater Studiorum - University of Bologna

• Tjitze Rienstra, Maastricht University

• Livio Robaldo, University of Swansea

• Arianna Rossi, Sant'Anna School of Advanced Studies

• Amir Sartipi, University of Luxembourg

• Ephraim Sinyabe, University of Ngaoundere

• Francesco Sovrano, University of Zurich

• Stefano Tedeschi, Università della Valle d'Aosta - Université de la Vallée d'Aoste

• Zhi Yan, University of Technology of Belfort-Montbéliard (UTBM)

• Qianbo Zang, Université du Luxembourg

Publication

All accepted papers will be published in the Springer proceedings Communications in Computer and Information Science (CCIS) series devoted to the publication of proceedings of computer science conferences.

Venue

Kyoto, Japan | November 18-24, 2024.

In conjunction with the The 25th International Conference on Principles and Practice of Multi-Agent Systems PRIMA 2024