Latent Space Policies for Hierarchical Reinforcement Learning.
Tuomas HaarnojaKristian HartikainenPieter AbbeelSergey LevinePublished in: CoRR (2018)
Keyphrases
- hierarchical reinforcement learning
- latent space
- latent variables
- low dimensional
- reinforcement learning
- generative model
- feature space
- gaussian process
- parameter space
- lower dimensional
- dimensionality reduction
- matrix factorization
- state abstraction
- manifold learning
- high dimensional
- probabilistic latent semantic analysis
- transfer learning
- model free
- distance metric
- reward function
- gaussian process latent variable models
- gaussian processes
- high dimensional data
- gaussian mixture
- probabilistic model
- data mining
- high dimensional spaces
- infinite horizon
- principal component analysis
- pattern recognition
- machine learning
- data sets