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What is Differentiable Simulation for Queue Control about?

The document presents a scalable framework for policy optimization in queuing network control using differentiable discrete event simulation, addressing challenges like high stochasticity and large state spaces. The proposed PATHWISE gradient estimator significantly improves sample efficiency, achieving 50-1000x better performance compared to traditional reinforcement learning methods. Additionally, a new work-conserving policy architecture enhances stability during training, making the approach suitable fo

Author

Shoumik Deb Nath

Language

EN