91 citations · 242 across the 32 of their papers we have counts for
14 papers · 1 filter
Learning Human Objectives by Evaluating Hypothetical Behavior
Siddharth Reddy, Anca D. Dragan, Sergey Levine +2
We seek to align agent behavior with a user's objectives in a reinforcement learning setting with unknown dynamics, an unknown reward function, and unknown unsafe states. The user…
Nonverbal Robot Feedback for Human Teachers
Sandy H. Huang, Isabella Huang, Ravi Pandya +1
Robots can learn preferences from human demonstrations, but their success depends on how informative these demonstrations are. Being informative is unfortunately very challenging,…
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…
On the Utility of Learning about Humans for Human-AI Coordination
Micah Carroll, Rohin Shah, Mark K. Ho +4
While we would like agents that can coordinate with humans, current algorithms such as self-play and population-based training create agents that can coordinate with themselves. Ag…
Scaled Autonomy: Enabling Human Operators to Control Robot Fleets
Gokul Swamy, Siddharth Reddy, Sergey Levine +1
Autonomous robots often encounter challenging situations where their control policies fail and an expert human operator must briefly intervene, e.g., through teleoperation. In sett…
Efficient Iterative Linear-Quadratic Approximations for Nonlinear Multi-Player General-Sum Differential Games
David Fridovich-Keil, Ellis Ratner, Lasse Peters +2
Many problems in robotics involve multiple decision making agents. To operate efficiently in such settings, a robot must reason about the impact of its decisions on the behavior of…