8 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 8 cited
Benchmarks and Algorithms for Offline Preference-Based Reward Learning
Daniel Shin, Anca D. Dragan, Daniel S. Brown
Learning a reward function from human preferences is challenging as it typically requires having a high-fidelity simulator or using expensive and potentially unsafe actual physical…
cs.RO2021★ 8 cited
Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments
Nitish Dashora, Daniel Shin, Dhruv Shah +5
Geometric methods for solving open-world off-road navigation tasks, by learning occupancy and metric maps, provide good generalization but can be brittle in outdoor environments th…
cs.LG2021★ 2 cited
Offline Preference-Based Apprenticeship Learning
Daniel Shin, Daniel S. Brown, Anca D. Dragan
Learning a reward function from human preferences is challenging as it typically requires having a high-fidelity simulator or using expensive and potentially unsafe actual physical…