GPDS: A multi-agent deep reinforcement learning game for anti-jamming secure computing in MEC network

Miaojiang Chen, Wei Liu, Ning Zhang, Junling Li, Yingying Ren, Meng Yi, Anfeng Liu

Abstract: Highlights•We first model the MEC anti-jammer as a multi-user continuous game.•A post decision state is proposed to deal with dynamic unknown information.•A minimax gradient strategy is proposed to realize learning generalization.•State-of-the-art methods are outperformed in both parameters and performance.