Variational Inference MPC for Bayesian Model-based Reinforcement Learning.
Masashi OkadaTadahiro TaniguchiPublished in: CoRR (2019)
Keyphrases
- variational inference
- model based reinforcement learning
- bayesian inference
- posterior distribution
- markov decision processes
- probabilistic model
- topic models
- mixture model
- variational methods
- gaussian process
- latent dirichlet allocation
- closed form
- probabilistic graphical models
- probability distribution
- latent variables
- hyperparameters
- exponential family
- reinforcement learning
- prior information
- approximate inference
- factor graphs
- posterior probability
- parameter estimation
- hidden variables
- image segmentation
- state space
- gaussian processes
- bayesian framework
- generative model
- maximum a posteriori
- markov chain monte carlo
- first order logic
- knowledge representation
- prior knowledge
- conditional probabilities
- learning algorithm