A control-theoretic framework for analysis and design of networked systems with strategic agents via structured strategies

为了使现代社会网络正常运作，必须激励具有战略头脑的用户参与这些网络，自愿为集体利益采取行动。这种网络的示例出现在智能交通系统、电子商务、智能能源网和能源市场以及无线系统中的频谱分配中。这些系统正在通过不断扩大的电子连接和计算的使用而发生巨大的变化，因此可以应用越来越复杂的方法来设计这些网络。这个建议的目的是研究这些网络系统的随机动态系统的战略代理人有多个相互作用的部分信息的存在下，系统和对方。特别是，我们的目标是开发一个控制理论的框架，以推进这种系统的分析的最先进的状态，并设计新颖的激励计划，推动代理人的行动，实现理想的社会目标。该研究将与一个重要的教育和推广计划紧密结合，该计划包括两个重点领域：在跨学科研究中培训学生，包括本科生和代表性不足的少数民族;并以新课程开发和学生参与的形式广泛传播研究成果。该提案将追求两个协同的重点，一个侧重于分析，另一个侧重于设计。分析的重点包括调查的控制理论框架，这将使系统的评估代理的均衡策略和信念，通过建模他们的相互作用作为一个动态的不对称和不完美的信息博弈。具体来说，我们计划开发一个系统的方法来寻找完美的贝叶斯均衡广泛的一类动态博弈的不对称信息。相关的分析建立在博弈论，分散随机控制，马尔可夫决策过程和优化的基础上。我们设想了一个理论框架，支持分析工具的平衡评价很像马尔可夫决策过程的成熟的向后动态规划工具。设计主旨包括调查激励，诱导代理有一个平衡的行为符合社会最优目标，并开发新的动态机制设计方法。在这里，我们将建立在动态游戏的工作，探索应用系统的方法学开发的分析推力动态机制设计。具体来说，我们将调查间接的动态机制，适用于现实的模型与代理有大的私人类型集，但小的动作集。此外，我们将研究拉格朗日松弛方法，允许一个更简单和更一般的分析动态机制设计的时间平均约束。

For the proper functioning of modern societal networks it is critical to incentivize strategically minded users participating in these networks to voluntarily act in the interest of the collective. Examples of such networks arise in intelligent transportation systems, electronic commerce, smart energy grid and energy markets, and spectrum allocation in wireless systems. These systems are being dramatically transformed by the ever-expanding use of electronic connectivity and computation so that increasingly sophisticated approaches can be applied for engineering these networks. This proposal aims to study these networked systems as stochastic dynamical systems with strategic agents having multiple interactions in the presence of partial information about the system and each other. In particular, the goal is to develop a control-theoretic framework to advance the state of the art for the analysis of such systems, and also to design novel incentive schemes that drive the agents' actions towards desirable social objectives. The research will be tightly integrated with a significant education and outreach program consisting of two focus areas: training students, including undergraduates and underrepresented minorities, in interdisciplinary research; and broadly disseminating research outcomes in the form of new curricular development and student involvement. The proposal will pursue two synergistic thrusts, one focusing on analysis and the other on design. The analysis thrust consists of investigating a control-theoretic framework that will enable the systematic evaluation of the agents' equilibrium strategies and beliefs, by modeling their interactions as a dynamic game with asymmetric and imperfect information. Specifically, we plan to develop a systematic methodology for finding Perfect Bayesian Equilibria for a broad class of dynamic games with asymmetric information. The associated analysis builds upon foundations in game theory, decentralized stochastic control, Markov decision processes and optimization. We envision a theoretical framework that supports analytical tools for the evaluation of equilibria much like the well-established backward dynamic programming tools for Markov decision processes. The design thrust consists of investigating incentives that induce agents to have an equilibrium behavior consistent with a socially optimal objective, and developing new dynamic mechanism design methodologies. Here, we will build upon the work on dynamic games by exploring applications of the systematic methodology developed in the analysis thrust to dynamic mechanism design. Specifically, we will investigate indirect dynamic mechanisms that are appropriate for realistic models with agents having large private type-sets but small action sets. Furthermore, we will investigate Lagrangian relaxation methods that allow for an easier and more general analysis of dynamic mechanism design with time-average constraints.