TY - GEN
T1 - RADAR-X
T2 - 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022
AU - Valmeekam, Karthik
AU - Sreedharan, Sarath
AU - Sengupta, Sailik
AU - Kambhampati, Subbarao
N1 - Publisher Copyright:
© 2022, Association for the Advancement of Artificial Intelligence.
PY - 2022/6/13
Y1 - 2022/6/13
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85128402579&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85128402579&partnerID=8YFLogxK
U2 - 10.1609/icaps.v32i1.19837
DO - 10.1609/icaps.v32i1.19837
M3 - Conference contribution
AN - SCOPUS:85128402579
T3 - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
SP - 508
EP - 517
BT - Proceedings of the 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022
A2 - Kumar, Akshat
A2 - Thiebaux, Sylvie
A2 - Varakantham, Pradeep
A2 - Yeoh, William
PB - Association for the Advancement of Artificial Intelligence
Y2 - 13 June 2022 through 24 June 2022
ER -