Deep reinforcement learning approach with hybrid action space for mobile charging in wireless rechargeable sensor networks.
Chengpeng JiangWencong ChenXingcan ChenSen ZhangWendong XiaoPublished in: Expert Syst. Appl. (2024)
Keyphrases
- sensor networks
- action space
- network connectivity
- reinforcement learning
- mobile wireless
- mobile nodes
- state space
- markov decision processes
- state and action spaces
- mobile networks
- continuous state
- mobile devices
- real valued
- mobile sensor networks
- base station
- wireless sensor networks
- sensor data
- visual sensor networks
- wireless video
- action selection
- environmental monitoring
- mobile users
- wireless networks
- data gathering
- energy efficient
- sensor nodes
- continuous state spaces
- state action
- resource constrained
- wireless communication
- function approximators
- data streams
- single agent
- energy consumption
- multi hop
- communication cost
- underwater acoustic
- markov decision process
- energy efficiency
- function approximation
- routing protocol
- optimal policy
- dynamic programming
- data transmission
- multi agent
- mobile applications
- machine learning
- communication bandwidth
- stochastic processes
- ad hoc networks
- mobile computing
- reward function
- mobile ad hoc networks