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cs.LG2026
Mitigating Data Scarcity in Spaceflight Applications for Offline Reinforcement Learning Using Physics-Informed Deep Generative Models
Alex E. Ballentine, Nachiket U. Bapat, Raghvendra V. Cowlagi
The deployment of reinforcement learning (RL)-based controllers on physical systems is often limited by poor generalization to real-world scenarios, known as the simulation-to-real…
cs.LG2025
Synthetic Data Generation for Minimum-Exposure Navigation in a Time-Varying Environment using Generative AI Models
Nachiket U. Bapat, Randy C. Paffenroth, Raghvendra V. Cowlagi
We study the problem of synthetic generation of samples of environmental features for autonomous vehicle navigation. These features are described by a spatiotemporally varying scal…
cs.LG2025
Inverse Reinforcement Learning for Minimum-Exposure Paths in Spatiotemporally Varying Scalar Fields
Alexandra E. Ballentine, Raghvendra V. Cowlagi
Performance and reliability analyses of autonomous vehicles (AVs) can benefit from tools that ``amplify'' small datasets to synthesize larger volumes of plausible samples of the AV…