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Simulation for service function chain parititioninig based on multi agent reinforcement learning

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MChamith/SFCSimulation

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This project is a reimplementation of the paper titled "Deep Multi-Agent Reinforcement Learning With Minimal Cross-Agent Communication for SFC Partitioning"

Recrated Reward plot

reward

Reward Plot on paper reward2

Optimal percentage recreated

>results for optimal percentage

Optimal percentage on paper

>results for optimal percentage2

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Simulation for service function chain parititioninig based on multi agent reinforcement learning

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