Explaining Plan Quality Differences

Published: 12 Feb 2024, Last Modified: 06 Mar 2024ICAPS 2024EveryoneRevisionsBibTeXCC BY 4.0
Keywords: Explainable AI Planning, Contrastive Explanation, Mixed-initiative
Abstract: In this paper we describe a method for explaining the differences between the quality of plans produced for similar planning problems. The method exploits a process of abstracting away details of the planning problems until the difference in the quality of the solutions they support has been minimised. We give a general definition of a valid abstraction of a planning problem. We then give the details of the implementation of a number of useful abstractions. Finally, we present a depth-bounded breadth-first search algorithm for finding suitable abstractions for explanations; and detail the results of an evaluation of the approach.
Primary Keywords: Human-aware Planning and Scheduling
Category: Long
Student: Graduate
Submission Number: 142