Abstract
Several research works have applied Reinforcement Learning (RL) algorithms to solve the Rate Adaptation (RA) problem in Wi-Fi networks. The dynamic nature of the radio link requires the algorithms to be responsive to changes in link quality. Delays in the execution of the algorithm due to implementional details may be detrimental to its performance, which in turn may decrease network performance. These delays can be avoided to a certain extent. However, this aspect has been overlooked in the state of the art when using simulated environments, since the computational delays are not considered. In this paper, we present an analysis of computational delays and their impact on the performance of RL-based RA algorithms, and propose a methodology to incorporate the experimental computational delays of the algorithms from running in a specific target hardware, in a simulation environment. Our simulation results considering the real computational delays showed that these delays do, in fact, degrade the algorithm’s execution and training capabilities which, in the end, has a negative impact on network performance.

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This study aims to conduct a bibliometric analysis inherent to assessing competitive intelligence and business intelligence concepts using the Scopus database and the Bibliometrix R software. The study's articles were found using precise criteria in the Scopus database. The 42 publications were then examined with Bibliometrix software, which included extensive parameterization for each component under evaluation. The results of this study consisted of establishing the number of existing publications on the topic under analysis between 2017 and 2021 - in this sense, it was possible to identify that the publications are experiencing an annual decrease rate of 22.69%; the trends in terms of publications and collaborations between countries; the most relevant journals in the area; and the interconnections between authors, keywords, and publications. This study has as an added value the possibility to evaluate the relevance attributed by academics to ascertain the most important contributions in terms of authors, articles, and journals. One major limitation in this study could be addressed in future research. The study focused on a limited study field in the context of business, management, and accounting, so it would be very pertinent to understand how this topic has evolved, particularly in the area of computer science.

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[No abstract available]