53 citations · 232 across the 44 of their papers we have counts for
8 papers · 1 filter
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…
Few Shot Speaker Recognition using Deep Neural Networks
Prashant Anand, Ajeet Kumar Singh, Siddharth Srivastava +1
The recent advances in deep learning are mostly driven by availability of large amount of training data. However, availability of such data is not always possible for specific task…
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…
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles
Siddharth Srivastava, Frederic Jurie, Gaurav Sharma
We address the problem of 3D object detection from 2D monocular images in autonomous driving scenarios. We propose to lift the 2D images to 3D representations using learned neural…
DeepPoint3D: Learning Discriminative Local Descriptors using Deep Metric Learning on 3D Point Clouds
Siddharth Srivastava, Brejesh Lall
Learning local descriptors is an important problem in computer vision. While there are many techniques for learning local patch descriptors for 2D images, recently efforts have bee…
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…
Learn and Link: Learning Critical Regions for Efficient Planning
Daniel Molina, Kislay Kumar, Siddharth Srivastava
This paper presents a new approach to learning for motion planning (MP) where critical regions of an environment are learned from a given set of motion plans and used to improve pe…