activity
20152021
most citedInteractive Plan Explicability in Human-Robot Teaming

6 citations · 13 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO20211 cited

Generating Active Explicable Plans in Human-Robot Teaming

Akkamahadevi Hanni, Yu Zhang

Intelligent robots are redefining a multitude of critical domains but are still far from being fully capable of assisting human peers in day-to-day tasks. An important requirement…

cs.AI2020

Domain Concretization from Examples: Addressing Missing Domain Knowledge via Robust Planning

Akshay Sharma, Piyush Rajesh Medikeri, Yu Zhang

The assumption of complete domain knowledge is not warranted for robot planning and decision-making in the real world. It could be due to design flaws or arise from domain ramifica…

cs.AI2020

Order Matters: Generating Progressive Explanations for Planning Tasks in Human-Robot Teaming

Mehrdad Zakershahrak, Shashank Rao Marpally, Akshay Sharma +2

Prior work on generating explanations in a planning and decision-making context has focused on providing the rationale behind an AI agent's decision making. While these methods pro…

cs.AI2019

Online Explanation Generation for Human-Robot Teaming

Mehrdad Zakershahrak, Ze Gong, Nikhillesh Sadassivam +1

As AI becomes an integral part of our lives, the development of explainable AI, embodied in the decision-making process of an AI or robotic agent, becomes imperative. For a robotic…

cs.AI20194 cited

Progressive Explanation Generation for Human-robot Teaming

Yu Zhang, Mehrdad Zakershahrak

Generating explanation to explain its behavior is an essential capability for a robotic teammate. Explanations help human partners better understand the situation and maintain trus…

cs.RO20196 cited

Interactive Plan Explicability in Human-Robot Teaming

Mehrdad Zakershahrak, Yu Zhang

Human-robot teaming is one of the most important applications of artificial intelligence in the fast-growing field of robotics. For effective teaming, a robot must not only maintai…