Towards Exploiting Generic Problem Structures in Explanations for Automated Planning

Alan Lindsay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Explainable AI is becoming an area of key focus in Artificial Intelligence. Within Automated Planning (AP) the area Explainable Planning (XAIP) focuses on explanations of the planning process. The relative transparency and flexibility of the planning process have been identified as key aspects suggesting that AP is well positioned to make an important contribution in Explainable AI [8]. However, there is still a wide gap between explanations that can be directly extracted from AP models and effective explanations. There are a growing number of frameworks that are considering the problem from both the user side, where it is interesting to understand the form that an explanation might take; as well as the planner side, which must be able to explain various decisions and related properties. However, approaches have focused on single domain settings, where substantial domain specific content is produced, or at a general level, where only abstract planning concepts can be used. We aim to develop an abstraction layer that sits between these and exploits the often overlapping concepts and structures that exist between many planning domains. We propose exploiting domain analysis techniques in order to identify common roles and generic problem structures (GPSs). By attaching the concepts used for explanation to these structures we can exploit the contextual information supported by the structure, and also reduce the burden of constructing explanations in domains where these structures exist. In this work we explore the opportunities for exploiting GPSs in XAIP.
Original languageEnglish
Title of host publicationK-CAP 2019 - Proceedings of the 10th International Conference on Knowledge Capture
PublisherAssociation for Computing Machinery (ACM)
Pages235-238
Number of pages4
ISBN (Electronic)9781450370080
ISBN (Print)9781450370080
DOIs
Publication statusPublished - 23 Sep 2019
Event10th International Conference on Knowledge Capture - Marina del Rey Marriott, Marina Del Rey, United States
Duration: 19 Nov 201921 Nov 2019
Conference number: 10
http://www.k-cap.org/2019/index.html

Conference

Conference10th International Conference on Knowledge Capture
Abbreviated titleK-CAP 2019
Country/TerritoryUnited States
CityMarina Del Rey
Period19/11/1921/11/19
Internet address

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