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Found 6 papers, 1 papers with code
Globally Stable Neural Imitation Policies
Imitation learning presents an effective approach to alleviate the resource-intensive and time-consuming nature of policy learning from scratch in the solution space.
Improving Generalization in Reinforcement Learning Training Regimes for Social Robot Navigation
We propose a method to improve the generalization performance of RL social navigation methods using curriculum learning.
Learning Agile Paths from Optimal Control
Efficient motion planning algorithms are of central importance for deploying robots in the real world.
A Library for Constraint Consistent Learning
This paper introduces the first, open source software library for Constraint Consistent Learning (CCL).
Learning Null Space Projections in Operational Space Formulation
In this paper, we consider learning the null space projection matrix of a kinematically constrained system in the absence of any prior knowledge either on the underlying policy, the geometry, or dimensionality of the constraints.
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors
An accurate model of patient survival time can help in the treatment and care of cancer patients.
