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Found 5 papers, 1 papers with code
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning
We construct a new continuous-time dynamical system, where the inputs are the observations of human behavior, and the dynamics include how the belief over the model parameters change.
Efficient Iterative Linear-Quadratic Approximations for Nonlinear Multi-Player General-Sum Differential Games
We benchmark our method in a three-player general-sum simulated example, in which it takes < 0. 75 s to identify a solution and < 50 ms to solve warm-started subproblems in a receding horizon.
Systems and Control Robotics Systems and Control
Few-Shot Intent Inference via Meta-Inverse Reinforcement Learning
A significant challenge for the practical application of reinforcement learning toreal world problems is the need to specify an oracle reward function that correctly defines a task.
Simplifying Reward Design through Divide-and-Conquer
Designing a good reward function is essential to robot planning and reinforcement learning, but it can also be challenging and frustrating.
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
A significant challenge for the practical application of reinforcement learning in the real world is the need to specify an oracle reward function that correctly defines a task.
