A lexicographic approach to constrained MDP admission control |
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Authors: | Martina Panfili Guido Oddi Vincenzo Suraci |
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Affiliation: | Department of Computer, Control and Management Engineering “Antonio Ruberti”, University of Rome “Sapienza”, Rome, Italy |
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Abstract: | This paper proposes a reinforcement learning-based lexicographic approach to the call admission control problem in communication networks. The admission control problem is modelled as a multi-constrained Markov decision process. To overcome the problems of the standard approaches to the solution of constrained Markov decision processes, based on the linear programming formulation or on a Lagrangian approach, a multi-constraint lexicographic approach is defined, and an online implementation based on reinforcement learning techniques is proposed. Simulations validate the proposed approach. |
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Keywords: | stochastic control Markov decision processes reinforcement learning communication networks call admission control |
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