2 citations · 3 across the 8 of their papers we have counts for
8 papers
ESAM++: Efficient Online 3D Perception on the Edge
Qin Liu, Lavisha Aggarwal, Saptarashmi Bandyopadhyay +4
Online 3D scene perception in real time is essential for robotics, AR/VR, and autonomous systems, particularly in edge computing scenarios where computational resources are limited…
Social Cooperation in Conversational AI Agents
Mustafa Mert Çelikok, Saptarashmi Bandyopadhyay, Robert Loftin
The development of AI agents based on large, open-domain language models (LLMs) has paved the way for the development of general-purpose AI assistants that can support human in tas…
YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks
Saptarashmi Bandyopadhyay, Vikas Bahirwani, Lavisha Aggarwal +3
Multimodal AI Agents are AI models that have the capability of interactively and cooperatively assisting human users to solve day-to-day tasks. Augmented Reality (AR) head worn dev…
On the Complexity of Learning to Cooperate with Populations of Socially Rational Agents
Robert Loftin, Saptarashmi Bandyopadhyay, Mustafa Mert Çelikok
Artificially intelligent agents deployed in the real-world will require the ability to reliably \textit{cooperate} with humans (as well as other, heterogeneous AI agents). To provi…
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
Alexander Rutherford, Benjamin Ellis, Matteo Gallici +18
Benchmarks are crucial in the development of machine learning algorithms, with available environments significantly influencing reinforcement learning (RL) research. Traditionally,…
Targets in Reinforcement Learning to solve Stackelberg Security Games
Saptarashmi Bandyopadhyay, Chenqi Zhu, Philip Daniel +3
Reinforcement Learning (RL) algorithms have been successfully applied to real world situations like illegal smuggling, poaching, deforestation, climate change, airport security, et…