A Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes.
Tuyen Pham LeNgo Anh VienTaeChoong ChungPublished in: IEEE Access (2018)
Keyphrases
- partially observable markov decision processes
- finite state
- reinforcement learning
- planning under uncertainty
- belief state
- belief space
- continuous state
- dynamic programming
- dynamical systems
- decision problems
- markov decision processes
- markov chain
- partial observability
- planning problems
- partially observable stochastic games
- stochastic domains
- partially observable
- optimal policy
- multi agent
- dec pomdps
- state space
- approximate solutions
- infinite horizon
- machine learning
- sequential decision making problems
- model checking
- partially observable markov decision process
- predictive state representations
- partially observable domains
- point based value iteration
- data mining