NAEM: Noisy Attention Exploration Module for Deep Reinforcement Learning.
Zhenwen CaiFeifei LeeChunyan HuKoji KotaniQiu ChenPublished in: IEEE Access (2021)
Keyphrases
- reinforcement learning
- active exploration
- action selection
- model based reinforcement learning
- machine learning
- autonomous learning
- function approximation
- markov decision processes
- exploration exploitation
- noisy data
- reinforcement learning algorithms
- exploration strategy
- supervised learning
- focus of attention
- information visualization
- multi agent
- exploration exploitation tradeoff
- optimal policy
- visual attention
- state space
- data analysis
- real time