Managing engineering systems with large state and action spaces through deep reinforcement learning.
C. P. AndriotisK. G. PapakonstantinouPublished in: Reliab. Eng. Syst. Saf. (2019)
Keyphrases
- state and action spaces
- engineering systems
- reinforcement learning
- markov decision processes
- action space
- computational intelligence
- state space
- engineering problems
- markov decision problems
- average reward
- partially observable markov decision process
- optimal policy
- reinforcement learning algorithms
- policy iteration
- artificial intelligence
- model free
- partially observable
- temporal difference
- function approximation
- partially observable markov decision processes
- decision making