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<pre>
XCBR: Case-Based Reasoning for the
Explanation of Intelligent Systems
Co-Chairs
Juan A. Recio-García
University Complutense of Madrid, Spain

Belén Díaz-Agudo
University Complutense of Madrid, Spain

Derek Bridge,
University College Cork, Ireland


Programme Committee
Jakob Michael Schoenborn, DFKI / University of Hildesheim, Germany
David Leake, Indiana University Bloomington, USA
Enric Plaza, IIIA-CSIC, Spain
Jose Jorro-Aragoneses, Universidad Complutense de Madrid, Spain
Mark Keane UCD Dublin, Ireland


Preface
The problem of explainability in Artificial Intelligence is not new. But the rise of autonomous intelligent
systems has created the necessity to understand how these intelligent systems arrive at a solution,
prediction, recommendation, or decision. Helping users to reach this kind of understanding may promote
the reliability of these systems, for example.

The goal of Explainable Artificial Intelligence (XAI) is to create a suite of new or modified AI techniques that
produce explainable models that, when combined with effective explanation techniques, enable end-users
and system developers to understand, appropriately trust, and effectively manage the emerging generation
of Artificial Intelligence systems.

Case-Based Reasoning (CBR) systems play a dual role in XAI. On the one hand, CBR systems are AI
systems, with their own need for explanations. But, on the other hand, CBR offers a way to generate
explanations for other AI techniques. The CBR system can use previous experiences of interactive
explanations and exploit memory-based techniques to generate explanations for these other AI
techniques.

After the two successful previous XCBR workshops, one in 2018 in Stockholm, Sweden and the other in
2019, in Otzenhausen, Germany, this third workshop offered an opportunity for discussion of progress in
this field. The workshop program included an invited talk by Mark Keane in which Mark reviewed ways of
pairing deep learning systems with CBR for purposes of explanation and data augmentation. Then we
organized two sessions with seven presentations in total. This year most of the contributions were oriented
to applications of CBR for explanation in different domains, including reviews of existing libraries and
evaluation approaches. Besides, we included a contribution from the Health Workshop into our program.

We wish to thank all who contributed to the success of this workshop, especially the authors, the Program
Committee, and the editors of the workshop proceedings!

Juan A. Recio-García
Belén Díaz-Agudo
Derek Bridge


September 2021

</pre>