Optimization of Markov decision processes under the variance criterion.
Li XiaPublished in: Autom. (2016)
Keyphrases
- markov decision processes
- optimal policy
- state space
- finite state
- policy iteration
- transition matrices
- dynamic programming
- reinforcement learning
- risk sensitive
- reinforcement learning algorithms
- markov decision process
- decision theoretic planning
- model based reinforcement learning
- reachability analysis
- partially observable
- finite horizon
- average reward
- factored mdps
- average cost
- planning under uncertainty
- decision processes
- action sets
- state and action spaces
- action space
- decision problems
- reward function
- infinite horizon
- sufficient conditions