11 papers
Multi-Robot Coordination for Planning under Context Uncertainty
Pulkit Rustagi, Kyle Hollins Wray, Sandhya Saisubramanian
Real-world robots often operate in settings where objective priorities depend on the underlying context of operation. When the underlying context is unknown apriori, multiple robot…
Calibrating Biophysical Models for Grape Phenology Prediction via Multi-Task Learning
William Solow, Sandhya Saisubramanian
Accurate prediction of grape phenology is essential for timely vineyard management decisions, such as scheduling irrigation and fertilization, to maximize crop yield and quality. W…
A Hybrid Modeling Framework for Crop Prediction Tasks via Dynamic Parameter Calibration and Multi-Task Learning
William Solow, Paola Pesantez-Cabrera, Markus Keller +3
Accurate prediction of crop states (e.g., phenology stages and cold hardiness) is essential for timely farm management decisions such as irrigation, fertilization, and canopy manag…
Learning Transferable Latent User Preferences for Human-Aligned Decision Making
Alina Hyk, Sandhya Saisubramanian
Large language models (LLMs) are increasingly used as reasoning modules in many applications. While they are efficient in certain tasks, LLMs often struggle to produce human-aligne…
Adaptive Querying for Reward Learning from Human Feedback
Yashwanthi Anand, Nnamdi Nwagwu, Kevin Sabbe +2
Learning from human feedback is a popular approach to train robots to adapt to user preferences and improve safety. Existing approaches typically consider a single querying (intera…
Uncovering Systemic and Environment Errors in Autonomous Systems Using Differential Testing
Yashwanthi Anand, Rahil P Mehta, Manish Motwani +1
When an autonomous agent behaves undesirably, including failure to complete a task, it can be difficult to determine whether the behavior is due to a systemic agent error, such as…