EXPLAINS is part of IJCCI, the 18th International Joint Conference on Computational Intelligence. Registration to EXPLAINS allows free access to all other IJCCI conferences.
IJCCI 2026 will be held in conjunction with ICINCO 2026, CoopIS 2026, WEBIST 2026, IC3K 2026 and IN4PL 2026.
Registration to IJCCI allows free access to the ICINCO, CoopIS, WEBIST, IC3K and IN4PL conferences (as a non-speaker).
Exceptionally, speakers are allowed to present remotely if unable to travel to the venue (hybrid support).
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In the future people will collaborate more and more with machines to solve complex problems using AI techniques. Such a collaboration requires adequate communication, trust, clarity and understanding. eXplainable AI (XAI) aims at addressing such challenges by combining the best of symbolic AI and Machine Learning including neural models, evolutionary computing and fuzzy systems. Such topic has been studied for years by all different communities of AI, with different definitions, evaluation metrics, motivations and results. In addition to technology, this involves social and legal issues as well as a wide range of real-world applications and domains. Both interpretability by design methods and post-hoc methods for explaining complex models have been proposed and investigated. Research has also redirected its emphasis on the structure of explanations and human-centered Artificial Intelligence, recognizing that the ultimate users of interactive technologies are humans.
Francesco Marcelloni, University of Pisa, Italy
Kurosh Madani, University of Paris-EST Créteil (UPEC), FranceNiki van Stein, Leiden University, Netherlands
Lars Kotthoff, University of St Andrews, United KingdomHervé Panetto, University of Lorraine, FranceGabriella Casalino, Universita degli Studi di Bari, Italy
Chairs: Maïssa Abdallah and Daniela Barreiro Claro
Publications:
Proceedings will be submitted for evaluation for indexing by: