MetaE2RL: Toward Meta-Reasoning for Energy-Efficient Multigoal Reinforcement Learning With Squeezed-Edge You Only Look Once.
Mozhgan NavardiEdward HumesTejaswini ManjunathTinoosh MohseninPublished in: IEEE Micro (2023)
Keyphrases
- energy efficient
- reinforcement learning
- meta reasoning
- wireless sensor networks
- energy consumption
- sensor networks
- function approximation
- reinforcement learning algorithms
- state space
- model free
- energy efficiency
- data dissemination
- control knowledge
- learning algorithm
- markov decision processes
- routing protocol
- rl algorithms
- routing algorithm
- base station
- data transmission
- multi core architecture
- temporal difference
- optimal policy
- multi agent
- case based planning
- machine learning
- sensor nodes
- transfer learning
- open systems