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Authors
Advisor(s)
Abstract(s)
The use of mechanisms based on artificial intelligence techniques
to perform dynamic learning has received much attention recently
and has been applied in solving many problems. However, the convergence
analysis of these mechanisms does not always receive the same
attention. In this paper, the convergence of the mechanism using reinforcement
learning to determine the channel detection sequence in a
multi-channel, multi-user radio network is discussed and, through simulations,
recommendations are presented for the proper choice of the
learning parameter set to improve the overall reward. Then, applying the
related set of parameters to the problem, the mechanism is compared to
other intuitive sorting mechanisms.
Description
Keywords
Artificial intelligence Reinforcement learning Convergence analysis Channel detection sequence problem
Citation
Mendes, Andre C. (2021). Convergence of the reinforcement learning mechanism applied to the channel detection sequence problem. In Pereira, Ana I.; Fernandes, Florbela P.; Coelho, João Paulo; Teixeira, João Paulo; Pacheco, Maria F.; Alves, Paulo; Lopes, Rui Pedro (Eds.) Optimization, learning algorithms and applications: first International Conference, OL2A 2021. Cham: Springer Nature. p. 401-416. ISBN 978-3-030-91884-2
Publisher
Springer Nature