Learning optimal admission control in partially observable queueing networks

DOI10.1007/S11134-024-09917-YMaRDI QIDQ6623440

Bruno Gaujal, Louis-Sébastien Rebuffi, Jonatha Anselmi

Publication date: 24 October 2024

Published in: Queueing Systems (Search for Journal in Brave)

zbMATH Keywords

admission controlreinforcement learningproduct-form queueing networksNorton's theorem

Mathematics Subject Classification ID

Queueing theory (aspects of probability theory) (60K25) Queues and service in operations research (90B22) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Optimal stochastic control (93E20) Performance evaluation, queueing, and scheduling in the context of computer systems (68M20)

Cites Work

• Title not available (Why is that?)
• Event-based optimization of admission control in open queueing networks
• Efficiency of simulation in monotone hyper-stable queueing networks
• Near-optimal regret bounds for reinforcement learning
• On the Computational Complexity of Stochastic Controller Optimization in POMDPs
• The Complexity of Markov Decision Processes
• A generalisation of Norton's theorem for multiclass queueing networks
• Parametric Analysis of Queuing Networks
• Uniform Stability of Markov Chains
• THE OPTIMAL ADMISSION THRESHOLD IN OBSERVABLE QUEUES WITH STATE DEPENDENT PRICING
• Estimating Multiclass Service Demand Distributions Using Markovian Arrival Processes

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