E.g. for the Internet-of-unmanned aerial vehicles (UAVs) some challenges in broadcasting and from new points of view are explored. In this paper, first, we investigate a single broadcast transceiver. From a control of noisy-channel viewpoint, we consider: ( i ) Alice sends $\mathscr{X}$ to Bob as more efficient as possible while she wishes Bob not to get access to the private message $\mathscr{S}$ regarding the correlation between $\mathscr{S}$ and $\mathscr{X}$ $-$ i.e., Alice purposefully sends a turbulent-flow of the information to Bob; and ( ii ) where $(\Theta _{1};\Theta _{2})$ is the control-action-pair which actualise a pursuit-Evasion . We consider dissipativity in our system due to the memory effect relating to the previous states. We thus propose a federated-learning based Blahut-Arimoto algorithm while a 2-D dissipativity -theoretic continuous-Mean-Field-Game (MFG) is proposed with regard to (w.r.t.) a joint probability-distribution-function (PDF) of the population distribution $-$ relating to a continuous-control-law. We also analyse what if Alice is owed to multiple Bobs in a multi-user scenario which we apply a bankruptcy based $3-$ level nested game for.

中文翻译：

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对广播的新颖信息论博弈论见解


例如，对于无人机互联网，我们从新的角度探讨了广播方面的一些挑战。在本文中，我们首先研究单个广播收发器。从噪声信道控制的角度来看，我们考虑： ( i ) Alice 尽可能高效地向 Bob 发送 $\mathscr{X}$，同时她希望 Bob 不要访问私人消息 $\mathscr{S}$关于 $\mathscr{S}$ 和 $\mathscr{X}$ $-$ 之间的相关性，即 Alice 故意向 Bob 发送信息的湍流； ( ii ) 其中 $(\Theta _{1};\Theta _{2})$ 是实现追逐-躲避的控制-动作对。由于与先前状态相关的记忆效应，我们考虑系统中的耗散性。因此，我们提出了一种基于联邦学习的 Blahut-Arimoto 算法，同时提出了关于（wrt）联合概率分布函数（PDF）的二维耗散理论连续平均场博弈（MFG）人口分布 $-$ 与连续控制法相关。我们还分析了如果在多用户场景中 Alice 欠多个 Bob，我们会应用基于破产的 3 美元级别嵌套游戏。