MATE: A multi-agent reinforcement learning approach for Traffic Engineering in Hybrid Software Defined Networks.
Yingya GuoMingjie DingWeihong ZhouBin LinCen ChenHuan LuoPublished in: J. Netw. Comput. Appl. (2024)
Keyphrases
- artificial intelligence
- traffic engineering
- multi agent reinforcement learning
- metro ethernet
- multi agent learning
- network management
- quality of service
- ip networks
- data center
- differentiated services
- multi agent
- real time
- reinforcement learning
- end to end delay
- network traffic
- computer systems
- social networks
- wireless networks
- qos requirements
- learning agents
- multi agent systems
- cooperative
- atm networks
- data mining
- neural network