Decentralized optimization of dynamic multi-agent networks

如果我们可以通过设计简单的规则来局部指导单个网络节点的行为，从而保证复杂的、动态演化的网络的某些规定的全局行为，那会怎么样？ 诸如通信网络、电网、运输系统之类的系统都是包括经常以动态方式交互的许多子系统的网络的示例。这样的网络可以被认为是多代理网络，即，由许多相对简单的组件或“代理”组成的复杂的网络系统，这些组件仅感测其本地环境，并具有影响该环境的能力，以及在其附近的其他代理。对这种网络系统的集中控制是不可能的，但我们对保证其稳健运行的需求变得至关重要。 我们的目标是发展一个理论，对他们的分散优化和控制。这样的理论还不存在，它是一个长期的，但它是可以实现的。 博弈论和最优化都是可以进行设计的强大框架。无论具体的应用领域，目标是为各个代理或子系统设计本地控制策略，以确保集体行为相对于系统目标是期望的。 长期目标是有一个理论的分散优化的动态多智能体网络系统。由于其抽象的力量，这种研究适用于不同的领域和潜在的变革。

What if we could guarantee some prescribed global behavior of complex, dynamically evolving networks by devising simple rules that locally guide the behavior of individual network nodes? Systems such as communication networks, power grids, transportation systems are all examples of networks comprising many sub-systems that often interact in dynamic ways. Such networks can be regarded as multi-agent networks, i.e., complex, networked systems composed of many relatively simple components, or "agents", that sense only their local environment, and have the ability to affect it, and the other agents within their proximity. Centralized control of such networked systems impossible, yet our need to guarantee their robust operation is becoming vital. Our goal is to develop a theory towards their decentralized optimization and control. Such a theory does not exist yet, it is a long-time out, but it is achievable. Game theory and optimization are both powerful frameworks within which design can be done. Regardless of the specific application domain, the goal is to design local control policies for the individual agents or sub-systems to ensure that the collective behavior is desirable with respect to the system objective. The long-term goal is to have a theory for decentralized optimization of dynamic multi-agent networked systems. Because of its power of abstraction such research has applicability to diverse fields and the potential to be transformative.