1 citations · 2 across the 15 of their papers we have counts for
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Multi-Objective Multi-Agent Path Finding with Lexicographic Cost Preferences
Pulkit Rustagi, Kyle Hollins Wray, Sandhya Saisubramanian
Many real-world scenarios require multiple agents to coordinate in shared environments, while balancing trade-offs between multiple, potentially competing objectives. Current multi…
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…
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…
Learning with Expert Abstractions for Efficient Multi-Task Continuous Control
Jeff Jewett, Sandhya Saisubramanian
Decision-making in complex, continuous multi-task environments is often hindered by the difficulty of obtaining accurate models for planning and the inefficiency of learning purely…
WOFOSTGym: A Crop Simulator for Learning Annual and Perennial Crop Management Strategies
William Solow, Sandhya Saisubramanian, Alan Fern
We introduce WOFOSTGym, a novel crop simulation environment designed to train reinforcement learning (RL) agents to optimize agromanagement decisions for annual and perennial crops…
Multi-Objective Planning with Contextual Lexicographic Reward Preferences
Pulkit Rustagi, Yashwanthi Anand, Sandhya Saisubramanian
Autonomous agents are often required to plan under multiple objectives whose preference ordering varies based on context. The agent may encounter multiple contexts during its cours…