Collaborative Attack Sequence Generation Model Based on Multiagent Reinforcement Learning for Intelligent Traffic Signal System

Keyphrases

• Multi-agent Reinforcement Learning 100%
• Intelligent Traffic Light Control 100%
• Traffic Signal Systems 100%
• Collaborative Attacks 100%
• Sequence Generation Model 100%
• Attack Sequence 100%
• Data Spoofing 50%
• Delay Time 25%
• Paralysis 25%
• Congestion 25%
• Air Pollution 25%
• Multiple Intersections 25%
• State Space 25%
• Intelligent Transportation Systems 25%
• Automated Approach 25%
• Traffic Efficiency 25%
• Stealthiness 25%
• Spoofing Attack 25%
• Vehicle Traffic 25%
• Attack Ratio 25%
• Reward Function 25%
• Action Space 25%
• Single Vehicle 25%
• VISSIM 25%
• Multi-actor 25%
• Attack Model 25%
• Partially Observable Markov Decision Process 25%
• Traffic Delay 25%
• Multi-vehicle 25%
• Traffic Simulation 25%
• Efficient Attack 25%
• Single Intersection 25%
• Collaborative Data 25%
• Actor-critic 25%
• Multi-agent Reinforcement Learning Algorithm 25%
• Multimodal Traffic 25%
• Stealthy Attacks 25%

Computer Science

• Reinforcement Learning 100%
• multi-agent 100%
• Traffic Signal 100%
• Generation Model 100%
• Collaboration 100%
• Spoofing Attack 60%
• time-delay 20%
• State Space 20%
• Air Pollution 20%
• Markov Decision Process 20%
• Stealthy Attack 20%
• Intelligent Transportation System 20%