3nd International Workshop on
EXplainable TRAnsparent AI and Multi-Agent Systems
(EXTRAAMAS 2020)


#Important Dates
Deadline for Submissions: 1 March 2021
Notification of acceptance: 20 March 2021
Camera-ready: 20 May 2021
Workshop day: 5-7 May 2021


#Call for Papers
The aim of the workshop is to gather researchers interested in developing an explainable agency for goal-oriented agents and robots supported by machine learning mechanisms. In particular, participants are invited to submit papers addressing whichever phase of explainability (e.g., generation, communication, and reception) fostering transparency in Autonomous Agents and Multi-Agent Systems (MAS) and robots. Compliance with such requirements is becoming necessary in most systems where agent-oriented approaches are increasingly employed.

Therefore, the purpose of this second “International workshop on Explainable Intelligence in Autonomous Agent and Multi-Agent Systems” (EXTRAAMAS) is five-fold:
- To strengthen the common ground for the study and development of explainable and understandable autonomous agents, robots, and Multi-Agent Systems (MAS),
- To explore how agent explainability and machine learning interpretability can be combined to achieve systems capable of both perceptual data-driven and cognitive goal driven explainability
- To investigate the potential of agent-based systems in the development of personalized user-aware explainable AI,
- To assess the impact of transparent and explained solutions on the user/agents behaviors,
- To discuss motivating examples and concrete applications in which the lack of explainability leads to problems, which would be resolved by explainability,
- To assess and discuss the first demonstrators and proof of concepts paving the way for the next generation systems,
To explore the potential of goal-driven XAI for industrial exploitation.




## Topics of EXTRAAMAS (non-exclusive list) ##

# Special Focus: Explainable Reasoning in Face of Contradictions
- Principle-based symbolic reasoning and explainable loop-busting
- XAI and formal models of human reasoning
- Neuro-symbolic approaches to explainable and principle-based reasoning
- Principle-based and explainable legal reasoning
- Other cross-disciplinary perspectives on explainable reasoning and contradiction
resolution

# Explainable Agents and Robots
- Explainable agent architectures
- Personalized XAI
- Explainable & Expressive robots
- Explainable human-robot collaboration
- Reinforcement Learning Agents
- Multi-modal explanations

# XAI & Ethics
- Social XAI
- AI, ethics, and explainability
- XAI vs AI

# XAI & MAS
- Multi-actors interaction in XAI
- XAI for agent/robots teams
- Simulations for XAI

# Interdisciplinary Aspects
- Cognitive and social sciences perspectives on explanations
- HCI for XAI
- Legal aspects of explainable agents
- Explanation visualization

# XAI Machine learning and Knowledge Representation
- Bridging symbolic and subsymbolic XAI
- Knowledge generation from interpretations
- Explanation visualization
- Explainable knowledge generation



# Workshop Chairs
Dr. Davide Calvaresi, HES-SO, Switzerland
Dr. Amro Najjar, University of Luxembourg, Luxembourg
Prof. Kary Främling, Umea University Sweden and Aalto University, Finland,
Prof. Michael Winikoff, Victoria University Wellington.
Dr. Tim Kampik, Umea University, Sweden, (industrial chair)

# Advisory Board
Dr. Tim Miller, School of Computing and Information Systems at The University of Melbourne.
Prof. Leon van der Torre, University of Luxembourg, Luxembourg
Prof. Virginia Dignum, Umea University, Sweden
Prof. Michael Ignaz Schumacher, HES-SO, Switzerland