53 citations · 136 across the 23 of their papers we have counts for
4 papers · 2 filters
Asking the Right Questions: Learning Interpretable Action Models Through Query Answering
Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava
This paper develops a new approach for estimating an interpretable, relational model of a black-box autonomous agent that can plan and act. Our main contributions are a new paradig…
Signaling Friends and Head-Faking Enemies Simultaneously: Balancing Goal Obfuscation and Goal Legibility
Anagha Kulkarni, Siddharth Srivastava, Subbarao Kambhampati
In order to be useful in the real world, AI agents need to plan and act in the presence of others, who may include adversarial and cooperative entities. In this paper, we consider…
Anytime Integrated Task and Motion Policies for Stochastic Environments
Naman Shah, Deepak Kala Vasudevan, Kislay Kumar +2
In order to solve complex, long-horizon tasks, intelligent robots need to carry out high-level, abstract planning and reasoning in conjunction with motion planning. However, abstra…
Why Couldn't You do that? Explaining Unsolvability of Classical Planning Problems in the Presence of Plan Advice
Sarath Sreedharan, Siddharth Srivastava, David Smith +1
Explainable planning is widely accepted as a prerequisite for autonomous agents to successfully work with humans. While there has been a lot of research on generating explanations…