The International Conference on Case-Based Reasoning (ICCBR) is the premier annual meeting of the case-based reasoning (CBR) community and the leading international conference on this topic. We welcome contributions from participants representing all types of affiliations (academic, industry, government) and from all communities applying CBR or conducting relevant research.

Conference submissions are not limited to papers on the conference theme, though the organizers are especially interested in papers that address the theme.

Generative AI and CBR

Generative AI and CBR is this year’s conference theme, directing the community’s attention to the growing pervasion of Generative AI in workplaces, homes, and societies, affecting us all. This year we pose the question:

    “What are some roles CBR can play to address some of the challenges stemming from Generative AI’s growing pervasion in our society?”

We encourage submissions and participation from members of the AI and CBR communities—whether they are researchers, policymakers, or practitioners—on the synergistic challenges between Generative AI and CBR. We look forward to a variety of submissions, including position papers, road mapping proposals, as well as traditional basic or applied research papers.

Topics of Interest

In addition to the emphasized areas above, we welcome submissions relevant to all areas of CBR, including (but not limited to):

Foundations

    Case authoring, elicitation, and visualization
    Case representation
    Case retrieval, indexing, and similarity measures
    Case reuse, adaptation, revision, and combination
    Case-base maintenance
    Confidence and uncertainty
    Evaluation, simulation, and prediction
    Explanations
    Similarity metric and adaptation knowledge learning

CBR and Related Fields

    ‘Modern’ CBR
    Analogical reasoning, cognitive models, and creative reasoning
    Cloud CBR
    Counterfactual learning and reasoning
    Explainable AI (XAI)
    Intelligent agents, perception, and action
    Internet of things
    Data mining and big data
    Machine learning (e.g., deep, instance-based/lazy, relational)
    Natural language processing and information retrieval
    Robotics and human-robot interaction
    Web CBR

CBR Tasks

    CBR planning
    Conversational CBR
    Design
    Distributed CBR
    Recommender systems
    Social CBR
    Temporal reasoning (e.g., reasoning with traces, time series)
    Textual CBR
    User modeling and personalization
    Workflow management and process-oriented CBR

CBR Systems and Applications

    AI for the Social Good
    CBR architectures and frameworks
    Cooking
    Diagnosis, technical support
    E-science, cyberinfrastructure, scientific workflows
    Economics, finance
    Education (including distance learning)
    Energy, logistics, traffic
    Game AI
    Knowledge and experience management
    Medicine, health
    Science, engineering