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07/11/2023
Deep Probabilistic Movement Primitives with a Bayesian Aggregator
Movement primitives are trainable parametric models that reproduce robot...
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12/06/2022
Variable-Decision Frequency Option Critic
In classic reinforcement learning algorithms, agents make decisions at d...
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02/04/2022
A Temporal-Difference Approach to Policy Gradient Estimation
The policy gradient theorem (Sutton et al., 2000) prescribes the usage o...
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12/22/2021
An Alternate Policy Gradient Estimator for Softmax Policies
Policy gradient (PG) estimators for softmax policies are ineffective wit...
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10/27/2020
Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient
Off-policy Reinforcement Learning (RL) holds the promise of better data ...
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10/26/2020
Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills
Parameterized movement primitives have been extensively used for imitati...
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02/26/2020
Dimensionality Reduction of Movement Primitives in Parameter Space
Movement primitives are an important policy class for real-world robotic...
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01/29/2020
An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions
The Nadaraya-Watson kernel estimator is among the most popular nonparame...
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01/08/2020
