RADAR-X: An Interactive Mixed Initiative Planning Interface Pairing Contrastive Explanations and Revised Plan Suggestions

Authors

  • Karthik Valmeekam Arizona State University
  • Sarath Sreedharan Arizona State University
  • Sailik Sengupta AWS AI Labs
  • Subbarao Kambhampati Arizona State University

Keywords:

Decision Support Systems, Automated Planning, Explainable AI Planning

Abstract

Decision support systems seek to enable informed decision-making. In the recent years, automated planning techniques have been leveraged to empower such systems to better aid the human-in-the-loop. The central idea for such decision support systems is to augment the capabilities of the human-in-the-loop with automated planning techniques and enhance the quality of decision-making. In addition to providing planning support, effective decision support systems must be able to provide intuitive explanations based on specific user queries for proposed decisions to its end users. Using this as motivation, we present our decision support system RADAR-X that showcases the ability to engage the user in an interactive explanatory dialogue by first enabling them to specify an alternative to a proposed decision (which we refer to as foils), and then providing contrastive explanations to these user-specified foils which helps the user understand why a specific plan was chosen over the alternative (or foil). Furthermore, the system uses this dialogue to elicit the user's latent preferences and provides revised plan suggestions through three different interaction strategies.

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Published

2022-06-13

How to Cite

Valmeekam, K., Sreedharan, S., Sengupta, S., & Kambhampati, S. (2022). RADAR-X: An Interactive Mixed Initiative Planning Interface Pairing Contrastive Explanations and Revised Plan Suggestions. Proceedings of the International Conference on Automated Planning and Scheduling, 32(1), 508-517. Retrieved from https://ojs.aaai.org/index.php/ICAPS/article/view/19837