Multi-Agent Reinforcement Learning Approach Scheduling for In-X Subnetworks

Computer Science

• Subnetwork 100%
• Multi-Agent Reinforcement Learning 100%
• Learning Approach 100%
• Deep Reinforcement Learning 60%
• Markov Decision Process 20%
• Reinforcement Learning 20%
• High Reliability 20%
• Candidate Action 20%
• Feed Forward Neural Networks 20%
• Feedforward Neural Network 20%

Chemical Engineering

• Reinforcement Learning 100%
• Feedforward Neural Network 50%