30 citations · 43 across the 13 of their papers we have counts for
5 papers · 1 filter
Symmetry Detection in Trajectory Data for More Meaningful Reinforcement Learning Representations
Marissa D'Alonzo, Rebecca Russell
Knowledge of the symmetries of reinforcement learning (RL) systems can be used to create compressed and semantically meaningful representations of a low-level state space. We prese…
Learning and Understanding a Disentangled Feature Representation for Hidden Parameters in Reinforcement Learning
Christopher Reale, Rebecca Russell
Hidden parameters are latent variables in reinforcement learning (RL) environments that are constant over the course of a trajectory. Understanding what, if any, hidden parameters…
Wide-Area Geolocalization with a Limited Field of View Camera
Lena M. Downes, Ted J. Steiner, Rebecca L. Russell +1
Cross-view geolocalization, a supplement or replacement for GPS, localizes an agent within a search area by matching images taken from a ground-view camera to overhead images taken…
Uncertainty Quantification for Competency Assessment of Autonomous Agents
Aastha Acharya, Rebecca Russell, Nisar R. Ahmed
For safe and reliable deployment in the real world, autonomous agents must elicit appropriate levels of trust from human users. One method to build trust is to have agents assess a…
Competency Assessment for Autonomous Agents using Deep Generative Models
Aastha Acharya, Rebecca Russell, Nisar R. Ahmed
For autonomous agents to act as trustworthy partners to human users, they must be able to reliably communicate their competency for the tasks they are asked to perform. Towards thi…