Title :
A lexicographie approach to constrained MDP Admission Control
Author :
Panfili, M. ; Pietrabissa, A.
Author_Institution :
Dept. of Comput., Control & Manage. Eng. A. Ruberti, Univ. of Rome Sapienza, Rome, Italy
Abstract :
This paper proposes a Reinforcement Learning-based lexicographic approach to the Call Admission Control (CAC) problem in communication networks. The CAC problem is modeled as a multi-constrained Markov Decision Problem (MDP). To overcome the problems of the standard approaches to the solution of constrained MDP, a multi-constraint lexicographic approach is defined, and an on-line implementation based on Reinforcement Learning techniques is proposed. Simulations validate the proposed approach.
Keywords :
Markov processes; decision theory; learning (artificial intelligence); telecommunication congestion control; telecommunication networks; CAC; MDP; call admission control; communication network; lexicographic approach; multiconstrained Markov Decision problem; multiconstraint lexicographic approach; reinforcement learning technique; Aerospace electronics; Computational modeling; Cost function; Markov processes; Process control; Standards; Vectors; Call Admission Control; Communication networks; Markov Decision Process; Stochastic control;
Conference_Titel :
Control & Automation (MED), 2013 21st Mediterranean Conference on
Conference_Location :
Chania
Print_ISBN :
978-1-4799-0995-7
DOI :
10.1109/MED.2013.6608908
