DRL4HFC: Deep Reinforcement Learning for Container-Based Scheduling in Hybrid Fog/Cloud System.
Ameni KallelMolka RekikMahdi KhemakhemPublished in: ICAART (2) (2024)
Keyphrases
- reinforcement learning
- container terminal
- state space
- scheduling algorithm
- learning algorithm
- single image
- function approximation
- scheduling problem
- round robin
- markov decision processes
- real time
- action selection
- hybrid learning
- parallel machines
- hybrid approaches
- resource allocation
- supervised learning
- dynamic programming
- multi agent
- transition model
- multi agent reinforcement learning
- scheduling strategy
- robotic control
- batch processing
- weather conditions
- temporal difference
- learning tasks
- optimal policy
- objective function
- machine learning