53 citations · 114 across the 11 of their papers we have counts for
6 papers · 1 filter
Multi-Agent Spectrum Sharing
Job Elliott, Graduate Student Member, IEEE +2
This project explores how multiple cognitive radars can learn to share limited wireless spectrum with other radio users without interfering with one another. Using machine learning…
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong-Ki Kim, Miao Liu, Matthew Riemer +6
A fundamental challenge in multiagent reinforcement learning is to learn beneficial behaviors in a shared environment with other simultaneously learning agents. In particular, each…
Robustness Analysis of Neural Networks via Efficient Partitioning with Applications in Control Systems
Michael Everett, Golnaz Habibi, Jonathan P. How
Neural networks (NNs) are now routinely implemented on systems that must operate in uncertain environments, but the tools for formally analyzing how this uncertainty propagates to…
Learning Hierarchical Teaching Policies for Cooperative Agents
Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei +7
Collective learning can be greatly enhanced when agents effectively exchange knowledge with their peers. In particular, recent work studying agents that learn to teach other teamma…
Context-Aware Pedestrian Motion Prediction In Urban Intersections
Golnaz Habibi, Nikita Jaipuria, Jonathan P. How
This paper presents a novel context-based approach for pedestrian motion prediction in crowded, urban intersections, with the additional flexibility of prediction in similar, but n…
A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries
Nikita Jaipuria, Golnaz Habibi, Jonathan P. How
This paper presents a novel framework for accurate pedestrian intent prediction at intersections. Given some prior knowledge of the curbside geometry, the presented framework can a…