Explainable Problem in clingo-dl Programs

Abstract

Research in explainable planning is becoming increasingly important as human-AI collaborations become more pervasive. An explanation is needed when the planning system’s solution does not match the human’s expectation. In this paper, we introduce the explainability problem in clingo-dl programs (XASP-D) because clingo-dl can effectively work with numerical scheduling, a problem similar to the explainable planning.