Jun 20, 2017 · We introduce a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks ...
We introduce a new formulation of the Hidden Parameter Markov Decision Pro- cess (HiP-MDP), a framework for modeling families of related tasks using low-.
Feb 12, 2017 · In this work, we apply a Gaussian Process latent variable model to jointly model the dynamics and the embedding, leading to a more elegant ...
We introduce a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks using ...
Feb 12, 2017 · In this work, we apply a Gaussian Process latent variable model to jointly model the dynamics and the embedding, leading to a more elegant ...
This work introduces a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks using ...
We introduce a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks using ...
Reviews: Robust and Efficient Transfer Learning with Hidden ...
proceedings.neurips.cc › paper › file
Summary: This paper presents a new transfer learning approach using Bayesian Neural Network in MDPs. They are building on the existing framework of Hidden ...
This paradigm of learning introduces an intriguing use case for transfer learn- ing. The Hidden Parameter Markov Decision Process (HiP-. MDP) (Doshi-Velez ...
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What is the hidden parameter Markov decision process?
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We introduce a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks using ...