Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
基本信息
- 批准号:RGPIN-2016-06414
- 负责人:
- 金额:$ 2.99万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2019
- 资助国家:加拿大
- 起止时间:2019-01-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Mean Field Games Theory (MFG) is perceived by numerous control theorists as probably the most important control theoretic development during the past decade. Canada's Caines, Huang and Malhamé acted as pioneers in the field (initial conference paper 2003), on this side of the Atlantic , while Lasry and Lions (a Fields medalist) did so in France, both independently with journal publications in the years 2006-2007. MFG is a control theory of large scale multi agent systems in a game situation, i.e. involving multiple and potentially conflicting optimizers. Such agents either have an intrinsic existence (e.g. an economy where individuals seek economic self fulfillment), or they may be deliberately created in a "divide to conquer" effort. This latter pattern is found in many large management or engineering systems where the major decision maker does not own the sensing, computation or communication capabilities, required to centrally control the system. Instead, the system is deliberately broken up into a set of local decision centers defined as agents, which may not have access to the same information sets, and which are assigned local performance functions. Provided both these functions and needed agent coordination signals are adequately engineered, the loss of optimality resulting from system breakup could be largely compensated by the corresponding decision making efficiency gains and lower communication costs. This is the essence of game theoretic based decentralized control of complex systems. However, computing different types of "equilibria" (generalizing notions of optimality) in games , particularly dynamic games, is notoriously difficult, with a difficulty generally compounded by the number of agents. The breakthrough made possible by MFG's is that of realizing that if agents share a lot of similarity, and the weight of an individual in the global welfare of the group vanishes as the number of agents increases without bound (e.g. an isolated individual's driving habits influence on the price of gasoline), the mass behavior (mean field) could become deterministic in the limit, even if individuals remain stochastic, as a result of pairs of individuals becoming gradually more independent, and the law of large numbers. It is a similar effect which is exploited in Statistical Mechanics analyses and indeed MFG's have emerged thanks to a blend of large interacting particle systems ideas, with the theory of Dynamic Games. Simply put, the virtual infinite agents game turns out to be much easier to analyze than its real large but finite game counterpart, and is used as a device to compute approximate equilibria.**We propose a two pronged research programme, theory / applications of MFGs. Two important applications are delineated: (i) Peak load shaving and improved renewables integration in smart grids; (ii) Biologically inspired collective decision making and navigation schemes in robotic systems. **
平均场博弈理论 (MFG) 被许多控制理论家认为可能是过去十年中最重要的控制理论发展,加拿大的 Caines、Huang 和 Malhamé 是该领域的先驱(2003 年首次会议论文)。 《Atlantic》,而 Lasry 和 Lions(菲尔兹奖获得者)则在法国这样做,两人在 2006-2007 年独立发表了期刊《MFG》是一种大规模多变量控制理论。博弈情境中的代理系统,即多个且可能相互冲突的优化器,或者涉及内在存在(例如,个体寻求经济自我实现的经济体),或者它们可能是在“分而治之”的努力中被故意创建的。后一种模式存在于许多大型管理或工程系统中,其中主要决策者不拥有集中控制系统所需的传感、计算或通信能力,而是故意将系统分解为一组定义的本地决策中心。作为代理人,可能不会可以访问相同的信息集,并且分配了本地性能功能,只要这些功能和所需的代理协调信号都得到充分设计,系统崩溃导致的最优性损失可以在很大程度上通过相应的决策效率增益和降低得到补偿。这是基于博弈论的复杂系统的分散控制的本质,但是,计算游戏中的不同类型的“均衡”(概括最优性概念)是非常困难的,而且通常会因复杂系统的复杂性而变得更加困难。 MFG 实现的突破在于认识到,如果代理具有很多相似性,那么随着代理数量无限制地增加,个体在群体整体福利中的权重就会消失(例如,孤立的个体的权重)。驾驶习惯对汽油价格的影响),即使个体仍然是随机的,大众行为(平均场)也可能在极限内变得确定性,因为成对的个体逐渐变得更加独立,并且大数定律是一个。类似的效果在统计力学分析中得到了利用,事实上 MFG 的出现得益于大型相互作用粒子系统思想与动态游戏理论的结合。简单地说,虚拟无限代理游戏比真实的大型游戏更容易分析。有限博弈对应物,并用作计算近似平衡的设备。**我们提出了一个双管齐下的研究计划,即 MFG 的理论/应用,其中描述了两个重要的应用:(i) 峰值负荷调节和改进的智能可再生能源整合。网格;(ii) 机器人系统中受生物学启发的集体决策和导航方案。
项目成果
期刊论文数量(0)
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Malhamé, Roland其他文献
Identification of hot water end-use process of electric water heaters from energy measurements
从能量测量识别电热水器热水最终使用过程
- DOI:
10.1016/j.epsr.2020.106625 - 发表时间:
2020-12 - 期刊:
- 影响因子:3.9
- 作者:
Khurram, Adil;Malhamé, Roland;Duffaut Espinosa, Luis;Almassalkhi, Mads - 通讯作者:
Almassalkhi, Mads
Malhamé, Roland的其他文献
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{{ truncateString('Malhamé, Roland', 18)}}的其他基金
Control of collective dynamics via mean field and and inverse mean field game theory
通过平均场和逆平均场博弈论控制集体动力学
- 批准号:
RGPIN-2022-05402 - 财政年份:2022
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Control of collective dynamics via mean field and and inverse mean field game theory
通过平均场和逆平均场博弈论控制集体动力学
- 批准号:
RGPIN-2022-05402 - 财政年份:2022
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2021
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2021
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2020
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2020
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2018
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2018
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2017
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
Mean Field Game Theory: A Potential Game Changer in the Decentralized Control of Complex Systems
平均场博弈论:复杂系统分散控制的潜在游戏规则改变者
- 批准号:
RGPIN-2016-06414 - 财政年份:2017
- 资助金额:
$ 2.99万 - 项目类别:
Discovery Grants Program - Individual
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