..., this study proposes the multi-queue Lyapunov-guided deep reinforcement learning (MQ-LyDRL) method to minimize task processing delay by jointly optimizing task offloading and resource allocation. This method innovatively integrates Lyapunov optimization with DRL . Specifically, by constructing Lyapunov...

... systems Deep reinforcement learning Target search National Key Research and Development Program of China 2022YFB4500900 With the development of artificial intelligence (Riedl, 2019), methods for learning autonomous behavioral strategies for agents (Hua et al., 2021...

... of the existing routing protocols under the condition of rapid data growth are elaborated, and the routing problem is remodeled as a Markov decision process. this paper aims to solve the problem of high blocking probability due to the increase in data volume by combining deep reinforcement learning. Finally...