Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processes

Code

• github.com/dtak/hip-mdp-public
  OfficialIn papertf★ 0

Abstract

We introduce a new formulation of the Hidden Parameter Markov Decision Process (HiP-MDP), a framework for modeling families of related tasks using low-dimensional latent embeddings. Our new framework correctly models the joint uncertainty in the latent parameters and the state space. We also replace the original Gaussian Process-based model with a Bayesian Neural Network, enabling more scalable inference. Thus, we expand the scope of the HiP-MDP to applications with higher dimensions and more complex dynamics.

Tasks

Reproductions