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cs.RO2019
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning
Somil Bansal, Andrea Bajcsy, Ellis Ratner +2
Real-world autonomous systems often employ probabilistic predictive models of human behavior during planning to reason about their future motion. Since accurately modeling human be…
cs.RO2018
Simplifying Reward Design through Divide-and-Conquer
Ellis Ratner, Dylan Hadfield-Menell, Anca D. Dragan
Designing a good reward function is essential to robot planning and reinforcement learning, but it can also be challenging and frustrating. The reward needs to work across multiple…