Mixed Reinforcement Learning with Additive Stochastic Uncertainty.
Yao MuShengbo Eben LiChang LiuQi SunBingbing NieBo ChengBaiyu PengPublished in: CoRR (2020)
Keyphrases
- reinforcement learning
- direct policy search
- stochastic nature
- partial observability
- stochastic approximation
- learning automata
- machine learning
- control policies
- reinforcement learning algorithms
- function approximation
- uncertain data
- stochastic simulation
- markov decision processes
- monte carlo
- state space
- stochastic optimization
- neural network
- robust optimization
- learning process
- multiattribute utility
- learning algorithm
- inherent uncertainty
- dynamic programming
- probability distribution
- temporal difference learning
- stochastic programming
- policy iteration
- stochastic model
- least squares
- temporal difference
- decision theory
- transfer learning