Making Sense of Reinforcement Learning and Probabilistic Inference.
Brendan O'DonoghueIan OsbandCatalin IonescuPublished in: CoRR (2020)
Keyphrases
- probabilistic inference
- reinforcement learning
- graphical models
- message passing
- influence diagrams
- approximate inference
- weighted model counting
- bayesian networks
- bayesian belief networks
- conditional probabilities
- belief networks
- context specific independence
- efficient inference
- bucket elimination
- variable elimination
- machine learning
- probabilistic reasoning
- exact inference
- optimal policy
- junction tree
- back propagation
- small number
- classification accuracy
- elimination algorithm
- dynamic programming
- learning algorithm