Ontology-Mediated Neurosymbolic Constraint Acquisition from Multiple Stakeholders

The paper introduces an architecture that bridges the gap between neural constraint sources and symbolic consumers by employing an OWL configuration ontology. It combines soft stakeholder preferences elicited by LLM assistants with hard hardware specifications, using description logic to detect unsatisfiability and produce symbolic explanations for interactive renegotiation. Remaining conflicts are addressed downstream through priority-based relaxation, demonstrated on a microgrid use case and positioned as broadly applicable to multi‑stakeholder domains.

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