Towards explainable AI planning as a service

Michael Cashmore, Anna Collins, Benjamin Krarup, Senka Krivic, Daniele Magazzeni, David Smith

Research output: Contribution to conferencePaper

1 Downloads (Pure)

Abstract

Explainable AI is an important area of research within which Explainable Planning is an emerging topic. In this paper, we argue that Explainable Planning can be designed as a service -- that is, as a wrapper around an existing planning system that utilises the existing planner to assist in answering contrastive questions. We introduce a prototype framework to facilitate this, along with some examples of how a planner can be used to address certain types of contrastive questions. We discuss the main advantages and limitations of such an approach and we identify open questions for Explainable Planning as a service that identify several possible research directions.
Original languageEnglish
Number of pages9
Publication statusPublished - 12 Jul 2019
Event2nd ICAPS Workshop on Explainable Planning - Berkeley, United States
Duration: 12 Jul 201912 Jul 2019

Conference

Conference2nd ICAPS Workshop on Explainable Planning
Abbreviated titleXAIP 2019
CountryUnited States
CityBerkeley
Period12/07/1912/07/19

    Fingerprint

Keywords

  • explainable AI
  • planning system
  • research

Cite this

Cashmore, M., Collins, A., Krarup, B., Krivic, S., Magazzeni, D., & Smith, D. (2019). Towards explainable AI planning as a service. Paper presented at 2nd ICAPS Workshop on Explainable Planning, Berkeley, United States.