In line with this year’s ICCBR conference theme, ”Generative AI and CBR”, the 3rd BEAR workshop focuses on foundational and practical advancements in Case-Based Reasoning (CBR), with a particular emphasis on complex and more expressive case representations. Traditional attribute-value structures are often limited in capturing the complexity of real-world domains suficiently. Therefore, this workshop addresses the need for advanced representations, such as object-oriented, textual, graphstructured, hierarchical, time-oriented, or hybrid forms, that enable more sophisticated reasoning and facilitate integration with other Artificial Intelligence (AI) methods.
These complex case representations raise significant methodological challenges across all phases of the CBR cycle, including retrieval, adaptation, revision, and retainment. They also open new opportunities for combining CBR with modern AI approaches (e.g., neural networks or large language models) in a principled way. The workshop invites contributions that explore these challenges through theoretical insights, system-oriented perspectives, or practical applications. Demonstrations and real-world use cases are particularly welcome to showcase the benefits and limitations of such representations in academic or practical settings.
Beyond paper presentations, the workshop places a strong emphasis on discussion and exchange. We explicitly encourage an interactive session in which participants share experiences, critically reflect on current methods, and explore directions for future research. Therefore, the BEAR workshop aims to foster collaboration within the community and stimulate new ideas to advance CBR beyond conventional paradigms.