Meta-Critic Reinforcement Learning for IOS-Assisted Multi-User Communications in Dynamic Environments.
Qinpei LuoBoya DiZhu HanPublished in: VTC2023-Spring (2023)
Keyphrases
- dynamic environments
- multi user
- reinforcement learning algorithms
- reinforcement learning
- actor critic
- multiple access
- function approximation
- temporal difference
- virtual environment
- reinforcement learning agents
- virtual world
- user interface
- multi granularity
- policy gradient
- multiple users
- augmented reality
- autonomous agents
- reinforcement learning methods
- mobile robot
- path planning
- model free
- single user
- state space
- single agent
- adaptive control
- markov decision processes
- real environment
- changing environment
- policy iteration
- autonomous systems
- evaluation function
- multi agent environments
- potential field
- communication networks
- agent systems
- multi agent
- communication systems
- collision avoidance
- learning algorithm
- gradient method
- function approximators
- approximate dynamic programming
- optimal policy
- plan execution
- three dimensional