On the Relationship Between KR Approaches for Explainable Planning
This paper addresses the problem of characterizing model reconciliation for explainable planning by relating existing KR techniques, which is an incremental contribution for researchers in explainable AI.
This paper expands a logic-based framework for the model reconciliation problem in explainable planning. It also details the relationship between KR techniques like abductive explanations and belief change, and their application to explainable planning.
In this paper, we build upon notions from knowledge representation and reasoning (KR) to expand a preliminary logic-based framework that characterizes the model reconciliation problem for explainable planning. We also provide a detailed exposition on the relationship between similar KR techniques, such as abductive explanations and belief change, and their applicability to explainable planning.