Outcome-Driven Reinforcement Learning via Variational Inference.
Tim G. J. RudnerVitchyr H. PongRowan McAllisterYarin GalSergey LevinePublished in: CoRR (2021)
Keyphrases
- variational inference
- reinforcement learning
- bayesian inference
- topic models
- posterior distribution
- gaussian process
- probabilistic graphical models
- latent dirichlet allocation
- mixture model
- variational methods
- closed form
- probabilistic model
- exponential family
- graphical models
- exact inference
- factor graphs
- state space
- approximate inference
- latent variables
- generative model
- machine learning
- hyperparameters
- gaussian distribution
- model selection