Meta-Reinforcement Learning in Non-Stationary and Dynamic Environments

Keyphrases

• Dynamic Environment 100%
• Task Representation 100%
• Meta-reinforcement Learning 100%
• Learning in Nonstationary Environments 100%
• Task Allocation 75%
• Stationary Environment 75%
• Well Structure 50%
• Structured Tasks 50%
• Training Data 25%
• Gaussian Mixture Model 25%
• Sampling Efficiency 25%
• Control Task 25%
• Artificial Agents 25%
• Amount of Training 25%
• Learning Strategies 25%
• Decision Task 25%
• Continual Learning 25%
• Training Strategy 25%
• Few-shot 25%
• Representation Learning 25%
• Asymptotic Performance 25%
• Learning Settings 25%
• Model of Models 25%
• Robotic Control 25%
• Non-stationary Environments 25%
• Few-shot Adaptation 25%
• Shared Structure 25%
• RL Algorithm 25%
• Deep Reinforcement Learning (deep RL) 25%
• Zero-shot 25%

Computer Science

• Reinforcement Learning 100%
• Dynamic Environment 100%
• Structured Task 100%
• Representation Learning 50%
• Deep Reinforcement Learning 50%
• Training Data 50%
• Decision-Making 50%
• Gaussian Mixture Model 50%
• Continual Learning 50%

Psychology

• Decision Making 100%
• Mixture Model 100%
• Gaussian Distribution 100%