Correction to: Task offloading for vehicular edge computing with edge‑cloud cooperation

World Wide Web https://doi.org/10.1007/s11280-022-01064-9 CORRECTION Correction to: Task offloading for vehicular edge computing with edge‑cloud cooperation Fei Dai1 · Guozhi Liu1 · Qi Mo2 · WeiHeng Xu1 · Bi Huang1 © Springer Science+Business Media, LLC, part of Springer Nature 2022 Correction to: World Wide Web https://doi.org/10.1007/s11280-022-01011-8 The original version of this article, unfortunately, contained mistakes. An error was found in the second to the last sentence of the Abstract. Instead of "Furthermore, the offloading scheme can be quickly learned by speeding up the convergence of the training process of DQN, which is good for fast offloading decisions.", it was captured as, "Furthermore, the learned offloading scheme can make fast by speeding up the convergence of the training process “to” the offloading scheme can be quickly learned by speeding up the convergence of the training process of DQN, which is good for fast offloading decisions." The original article has been corrected. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. The original article can be found online at https://doi.org/10.1007/s11280-022-01011-8. * Bi Huang Fei Dai Guozhi Liu Qi Mo WeiHeng Xu 1 School of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, China 2 School of Software, Yunnan University, Kunming, China 13 Vol.:(0123456789)  (...truncated)