Dynamics on Linear Influence Network Games Under Stochastic Environments
Dynamics on Linear Influence Network Games Under Stochastic Environments
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DOI：
10.1007/978-3-319-47413-7_7
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发表时间：
2016-11
期刊：
影响因子：
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通讯作者：
Zhengyuan Zhou;N. Bambos;P. Glynn
中科院分区：
文献类型：
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作者：
Zhengyuan Zhou;N. Bambos;P. Glynn
线性影响网络是风险管理中广泛适用的概念框架。它在计算机和网络安全方面有着重要的应用。针对这些风险管理应用的线性影响网络的先前工作一直集中在静态，一次性设置的均衡分析。此外，底层的网络环境也被假定为是确定性的，在本文中，我们解除这两个假设，并考虑一个公式的网络环境是随机的和时变的。特别是，我们研究了著名的最佳反应动力学的随机行为。具体来说，我们给出了解释和易于验证的充分条件下，我们建立的存在性和唯一性，以及收敛（指数收敛速度）的平稳分布相应的马尔可夫链。
A linear influence network is a broadly applicable conceptual framework in risk management. It has important applications in computer and network security. Prior work on linear influence networks targeting those risk management applications have been focused on equilibrium analysis in a static, one-shot setting. Furthermore, the underlying network environment is also assumed to be deterministic.In this paper, we lift those two assumptions and consider a formulation where the network environment is stochastic and time-varying. In particular, we study the stochastic behavior of the well-known best response dynamics. Specifically, we give interpretable and easily verifiable sufficient conditions under which we establish the existence and uniqueness of as well as convergence (with exponential convergence rate) to a stationary distribution of the corresponding Markov chains.