31 citations · 178 across the 53 of their papers we have counts for
9 papers · 1 filter
Cross-Loss Influence Functions to Explain Deep Network Representations
Andrew Silva, Rohit Chopra, Matthew Gombolay
As machine learning is increasingly deployed in the real world, it is paramount that we develop the tools necessary to analyze the decision-making of the models we train and deploy…
Learning from Suboptimal Demonstration via Self-Supervised Reward Regression
Letian Chen, Rohan Paleja, Matthew Gombolay
Learning from Demonstration (LfD) seeks to democratize robotics by enabling non-roboticist end-users to teach robots to perform a task by providing a human demonstration. However,…
FireCommander: An Interactive, Probabilistic Multi-agent Environment for Heterogeneous Robot Teams
Esmaeil Seraj, Xiyang Wu, Matthew Gombolay
The purpose of this tutorial is to help individuals use the \underline{FireCommander} game environment for research applications. The FireCommander is an interactive, probabilistic…
Human-Robot Team Coordination with Dynamic and Latent Human Task Proficiencies: Scheduling with Learning Curves
Ruisen Liu, Manisha Natarajan, Matthew Gombolay
As robots become ubiquitous in the workforce, it is essential that human-robot collaboration be both intuitive and adaptive. A robot's quality improves based on its ability to expl…
Meta-active Learning in Probabilistically-Safe Optimization
Mariah L. Schrum, Mark Connolly, Eric Cole +3
Learning to control a safety-critical system with latent dynamics (e.g. for deep brain stimulation) requires taking calculated risks to gain information as efficiently as possible.…
Coordinated Control of UAVs for Human-Centered Active Sensing of Wildfires
Esmaeil Seraj, Matthew Gombolay
Fighting wildfires is a precarious task, imperiling the lives of engaging firefighters and those who reside in the fire's path. Firefighters need online and dynamic observation of…
Four Years in Review: Statistical Practices of Likert Scales in Human-Robot Interaction Studies
Mariah L. Schrum, Michael Johnson, Muyleng Ghuy +1
As robots become more prevalent, the importance of the field of human-robot interaction (HRI) grows accordingly. As such, we should endeavor to employ the best statistical practice…
Heterogeneous Learning from Demonstration
Rohan Paleja, Matthew Gombolay
The development of human-robot systems able to leverage the strengths of both humans and their robotic counterparts has been greatly sought after because of the foreseen, broad-ran…
Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation
Letian Chen, Rohan Paleja, Muyleng Ghuy +1
Reinforcement learning (RL) has achieved tremendous success as a general framework for learning how to make decisions. However, this success relies on the interactive hand-tuning o…