Keyphrases
Multi-agent Reinforcement Learning
100%
Multi-domain
100%
Digital Twin
100%
Computing Power Network
100%
Service Function Chain
100%
Multi-agent Deep Deterministic Policy Gradient (MADDPG)
57%
Network Function Virtualization
42%
Energy Consumption
28%
Success Rate
14%
Mapping Problem
14%
Learning Framework
14%
Latency
14%
Physical Objects
14%
Numerical Experiments
14%
Power Link
14%
Reformation
14%
Delay Performance
14%
Load Balancing
14%
Network Layer
14%
Computing Power
14%
Physical Network
14%
Twin Network
14%
Centralized Training
14%
Link Bandwidth
14%
Energy Domain
14%
Prioritized Experience Replay
14%
Performance Verification
14%
Emerging Computing
14%
Decentralized Execution
14%
Virtual Twin
14%
Performance Upper Bound
14%
Virtual Replica
14%
Dynamic Service
14%
Domain Controller
14%
Cross-domain Services
14%
Reparameterization Trick
14%
Computer Science
Service Function
100%
Computing Power
100%
Digital Twin
100%
Multi-Agent Reinforcement Learning
100%
multi agent
57%
Network Function Virtualization
42%
Energy Consumption
28%
Learning Framework
14%
Physical Object
14%
End-to-End Delay
14%
Load Balancing
14%
Network Layer
14%
Link Bandwidth
14%
Reparameterization
14%
Domain Controller
14%
Physical Network
14%
Domain Service
14%