Explainable Artificial Intelligence for Training and Tutoring

  • Authors:

  • H. Chad Lane;Mark G. Core;Michael van Lent;Steve Solomon;Dave Gomboc

  • Affiliations:

  • University of Southern California / Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA 90292 USA, {lane, core, vanlent, solomon, gomboc}@ict.usc.edu;University of Southern California / Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA 90292 USA, {lane, core, vanlent, solomon, gomboc}@ict.usc.edu;University of Southern California / Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA 90292 USA, {lane, core, vanlent, solomon, gomboc}@ict.usc.edu;University of Southern California / Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA 90292 USA, {lane, core, vanlent, solomon, gomboc}@ict.usc.edu;University of Southern California / Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA 90292 USA, {lane, core, vanlent, solomon, gomboc}@ict.usc.edu

  • Venue:
  • Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
  • Year:
  • 2005

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Abstract

This paper describes an Explainable Artificial Intelligence (XAI) tool that allows entities to answer questions about their activities within a tactical simulation. We show how XAI can be used to provide more meaningful after-action reviews and discuss ongoing work to integrate an intelligent tutor into the XAI framework.