An XAI View on Explainable ASP: Methods, Systems, and Perspectives
A new survey paper examines Explainable AI (XAI) methods within Answer Set Programming (ASP), a symbolic AI approach. The paper categorizes different types of ASP explanations and maps them to user queries, evaluating the coverage provided by existing theories and tools. It also identifies current limitations and suggests future research directions in this area. AI
IMPACT Provides a structured overview of explainability techniques in symbolic AI, potentially guiding future research and development in interpretable AI systems.