Qinghua Li

Nov 13, 2024 | mdpi.com | Tianfeng Zhou |Cong Chen |Cong Dong |Qinghua Li

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Apr 28, 2024 | mdpi.com | Jing Zhao |Qinghua Li |Muhammad Zeeshan |Guoqiang Zhang

All articles published by MDPI are made immediately available worldwide under an open access license. No specialpermission is required to reuse all or part of the article published by MDPI, including figures and tables. Forarticles published under an open access Creative Common CC BY license, any part of the article may be reused withoutpermission provided that the original article is clearly cited. For more information, please refer tohttps://www.mdpi.com/openaccess.

Nov 22, 2023 | mdpi.com | Qinghua Li |Cong Chen

1. IntroductionAs a result of the advancement of industrial society and the affluence of people, the demand for goods and services is constantly increasing, leading to record-breaking carbon emissions released due to modern industry, which causes serious climate change problems [1,2,3]. As climate warming threatens the survival of humanity, numerous countries have initiated shifts in their conventional patterns of industrial development to promote the reduction of carbon emissions [4,5,6].

Aug 18, 2023 | mdpi.com | Yuangang Li |Tao Guo |Qinghua Li |Xinyue Liu

4.2. E2S2RND Algorithm Performance ExperimentWe conducted comparative experiments in the Montezuma’s Revenge experimental environment, mainly comparing the performance of E2S2RND and the original RND method, and the experimental results are shown in Figure 6. As can be seen from the figure, our proposed ESSRND method (green) and the auxiliary agent training framework E2S2RND (orange) have a significant performance improvement compared to the original RND method (red).