A reinforcement-learning approach for admission control in distributed network service systems

DOI10.1007/S10878-014-9820-3zbMath1343.90017OpenAlexW2072214598MaRDI QIDQ266057

Baoqun Yin, Xiaonong Lu, Haipeng Zhang

Publication date: 13 April 2016

Published in: Journal of Combinatorial Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10878-014-9820-3

zbMATH Keywords

admission controldistributed network service systempolicy switching mechanismreinforcement-learningSMDP

Mathematics Subject Classification ID

Stochastic network models in operations research (90B15) Queues and service in operations research (90B22) Markov and semi-Markov decision processes (90C40)

Cites Work

• A policy gradient method for semi-Markov decision processes with application to call admission control
• Reinforcement learning for long-run average cost.
• Basic ideas for event-based optimization of Markov systems
• A basic formula for performance gradient estimation of semi-Markov decision processes
• On optimal call admission control in resource-sharing system
• A basic formula for online policy gradient algorithms
• Applied Semi-Markov Processes
• Unnamed Item

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