Game Theory Algorithm of Reconfiguration for Shipboard Power System

船舶电力系统故障重构通过改变系统供电路径来恢复重要负载的供电，对增强系统的存活性有着重要意义。在多智能体（agent）架构的基础上，构建船舶电力系统博弈重构模型并提出求解方法。该模型以船舶电力系统中不同区域的agent作为博弈参与者，将船舶电力系统的重构问题转化为各agent之间的合作一竞争问题，从而保证重要负载的恢复供电。论文进一步提出该模型的求解算法，该算法首先判断博弈模式的合作与非合作属性，之后通过agent或agent联盟之间的博弈过程，计算各agent所属的负载／发电机的投切及转移策略。仿真算例表明，该算法能够快速有效地求解船舶电力系统重构问题，最大程度保证系统的存活性。

Hybrid Estimation of State and Input for Linear Discrete Time-varying Systems： A Game Theory Approach

为线性分离变化时间的系统的 H 混合评价问题在这份报纸被调查，在估计的信号是状态和输入的线性联合的地方。设计目的从骚乱要求最坏的精力获得到是的评价错误不到规定水平。混合评价问题的最佳的答案是僵绳点一二播放器零和微分游戏。根据微分比赛途径，为混合评价问题的必要、足够的可解决的条件以一个 Riccati 微分方程的答案被提供。而且，如果可解决的条件满足，一个可能的评估者被建议。评估者被印射矩阵的一个获得矩阵和产量描绘，在后者反映在未知输入和输出评价错误之间的内部关系的地方。最后，一个数字例子被提供说明建议途径。

Hybrid Estimation of State and Input for Linear Continuous Time-varying Systems:A Game Theory Approach

The H∞ hybrid estimation problem for linear continuous time-varying systems is in-vestigated in this paper, where estimated signals are linear combination of state and input. Designobjective requires the worst-case energy gain from disturbance to estimation error be less than a pre-scribed level. Optimal solution of the hybrid estimation problem is the saddle point of a two-playerzero sum di?erential game. Based on the di?erential game approach, necessary and su?cient solvableconditions for the hybrid estimation problem are provided in terms of solutions to a Riccati di?e-rential equation. Moreover, one possible estimator is proposed if the solvable conditions are satisfied.The estimator is characterized by a gain matrix and an output mapping matrix that re?ects theinternal relations between the unknown input and output estimation error. Both state and unknowninputs estimation are realized by the proposed estimator. Thus, the results in this paper are alsocapable of dealing with fault diagnosis problems of linear time-varying systems. At last, a numericalexample is provided to illustrate the proposed approach.

STRUCTURES OF VALUES FOR SET GAMES RESTRICTED BY PARTITION SYSTEM

A set game, in which the worth of a coalition is expressed by a set instead of a real number, is a new type of cooperative game. A F-restricted set game is a set game restricted by partition system. The main theorems show the structures of IM-value,OIM-value,SCM-value and ICM-value respectively,and the equivalency of IM value and the OIM-value for monotonic set games restricted by partition system as well.

Simulation for chaos game representation of genomes by recurrent iterated function systems

Chaos game representation (CGR) of DNA sequences and linked protein sequences from genomes was proposed by Jeffrey (1990) and Yu et al. (2004), respectively. In this paper, we consider the CGR of three kinds of sequences from complete genomes: whole genome DNA sequences, linked coding DNA sequences and linked protein sequences. Some fractal patterns are found in these CGRs. A recurrent iterated function systems (RIFS) model is proposed to simulate the CGRs of these sequences from genomes and their induced measures. Numerical results on 50 genomes show that the RIFS model can simulate very well the CGRs and their induced measures. The parameters estimated in the RIFS model reflect information on species classification.

NUMERICAL METHOD BASED ON HAMILTON SYSTEM AND SYMPLECTIC ALGORITHM TO DIFFERENTIAL GAMES

The resolution of differential games often concerns the difficult problem of two points border value （TPBV）, then ascribe linear quadratic differential game to Hamilton system. To Hamilton system, the algorithm of symplectic geometry has the merits of being able to copy the dynamic structure of Hamilton system and keep the measure of phase plane. From the viewpoint of Hamilton system, the symplectic characters of linear quadratic differential game were probed; as a try, Symplectic-Runge-Kutta algorithm was presented for the resolution of infinite horizon linear quadratic differential game. An example of numerical calculation was given, and the result can illuminate the feasibility of this method. At the same time, it embodies the fine conservation characteristics of symplectic algorithm to system energy.

基于演化博弈的我国分级诊疗策略分析

目的在分级诊疗制度中涉及政府、医院和患者之间的利益关系,探讨三方动态博弈策略,有利于完善分级诊疗的理论范式和政策逻辑。方法构建政府、医院和患者三方模型,分析其策略选择及演化路径,求解三方演化博弈的稳定策略,探究如何进行利益平衡和合作以实现三方共赢。另外,利用Matlab R2018b对模型进行仿真,进一步分析三方主体的演化路径以及不同策略选择对分级诊疗制度推广的影响。结果政府、医院和患者3个主体的决策行为之间相互影响,最终将演化至点(1,1,1)的理想稳定状态。增大政府补贴会加速医院和患者的初始参与概率值收敛至1,但过多的补贴会使政府逐渐背离鼓励分级诊疗的策略。结论政府应在成本范围内加大对医院优质医疗资源下沉的专家补贴力度,并加强政府监管。大型医院和基层医疗卫生机构重要的是实现医生资源的自由流动和合理分布。患者还需转变固有的就医观念,才能最终实现有序就医。

Spatial snowdrift game in heterogeneous agent systems with co-evolutionary strategies and updating rules

We propose an evolutionary snowdrift game model for heterogeneous systems with two types of agents, in which the inner-directed agents adopt the memory-based updating rule while the copycat-like ones take the unconditional imitation rule; moreover, each＇agent can change his type to adopt another updating rule once the number he sequentially loses the game at is beyond his upper limit of tolerance. The cooperative behaviors of such heterogeneous systems are then investigated by Monte Carlo simulations. The numerical results show the equilibrium cooperation frequency and composition as functions of the cost-to-benefit ratio r are both of plateau structures with discontinuous steplike jumps, and the number of plateaux varies non-monotonically with the upper limit of tolerance VT as well as the initial composition of agents faO. Besides, the quantities of the cooperation frequency and composition are dependent crucially on the system parameters including VT, faO, and r. One intriguing observation is that when the upper limit of tolerance is small, the cooperation frequency will be abnormally enhanced with the increase of the cost-to-benefit ratio in the range of 0 〈 r 〈 1/4. We then probe into the relative cooperation frequencies of either type of agents, which are also of plateau structures dependent on the system parameters. Our results may be helpful to understand the cooperative behaviors of heterogenous agent systems.

Dynamical Systems Theory Compared to Game Theory: The Case of the Salamis’s Battle

In this paper, we present an innovative non–linear, discrete, dynamical system trying to model the historic battle of Salamis between Greeks and Persians. September 2020 marks the anniversary of the 2500 years that have passed since this famous naval battle which took place in late September 480 B.C. The suggested model describes very well the most effective strategic behavior between two participants during a battle (or in a war). Moreover, we compare the results of the Dynamical Systems analysis to Game Theory, considering this conflict as a “war game”.

System dynamics of behaviour-evolutionary mix-game models

In real financial markets there are two kinds of traders： one is fundamentalist, and the other is a trend-follower. The mix-game model is proposed to mimic such phenomena. In a mix-game model there are two groups of agents： Group 1 plays the majority game and Group 2 plays the minority game. In this paper, we investigate such a case that some traders in real financial markets could change their investment behaviours by assigning the evolutionary abilities to agents： if the winning rates of agents are smaller than a threshold, they will join the other group; and agents will repeat such an evolution at certain time intervals. Through the simulations, we obtain the following findings： （i） the volatilities of systems increase with the increase of the number of agents in Group 1 and the times of behavioural changes of all agents; （ii） the performances of agents in both groups and the stabilities of systems become better if all agents take more time to observe their new investment behaviours; （iii） there are two-phase zones of market and non-market and two-phase zones of evolution and non-evolution; （iv） parameter configurations located within the cross areas between the zones of markets and the zones of evolution are suited for simulating the financial markets.

基于混合博弈的综合能源多园区运行策略研究

为了解决多园区综合能源系统联合调度运行后出现的复杂利益关系和隐私保护问题,提出一种基于博弈论的多园区分布式协调优化策略。由综合能源供应商作为上层领导者制定能源价格,引导下层园区运营商优化园区运行,构成主从博弈关系;下层园区以非合作博弈方式各自追求园区运行成本最小,并应用Kriging元模型结合粒子群算法,实现双层博弈模型的求解。通过算例对比分析,证明了所提多园区分布式协调优化策略可降低各园区的运行成本,并且综合能源供应商制定的能源定价策略也为自身带来了收益。

基于主从博弈的电热氢综合能源系统优化运行

针对综合能源系统(integrated energy system,IES)中各主体间交互关系复杂、利益冲突显著的问题,提出了基于主从博弈的电热氢综合能源系统优化调度模型。首先,在分析氢能“产消一体化”传输特性的基础上,构建计及氢能全过程充分利用的能源生产商(energy producer,EP)模型;其次,分析EP、负荷聚合商(load aggregator,LA)及能源销售商(energy system operator,ESO)之间的价格信息交互关系,考虑负荷聚合商在需求响应机制下的资源整合效用,建立IES中各利益主体的收益模型;最后,引入“主从博弈”思想,建立以ESO为主导者,采用遗传算法和二次规划相结合的方法,对以EP和LA为跟随者的一主多从Stackelberg博弈模型进行求解。以中国北部某地区的园区IES为例,验证了该模型在促进各主体间利益均衡及共同获利方面的有效性。

基于主从博弈的含碳捕集与热电联产综合能源系统优化运行

为了合理地分配综合能源系统中各主体之间的利益,促进能源低碳化,文中基于主从博弈框架建立了含碳捕集系统的综合能源系统优化调度模型,降低了热电联产机组的碳排放量和系统的运营成本。文章构建碳捕集、电转气和热电联产的联合运行模型,在考虑综合需求响应的基础上,建立综合能源系统各主体的收益模型;构建一主多从的Stackelberg博弈模型,由于构建的优化模型具有高维、非线性非凸的特点,数值方法难以求解,传统启发式算法容易陷入局部最优且收敛速度较慢,因此提出一种新型天牛郊狼算法结合二次规划的分布式算法。以北方某工业园区为算例进行验证,分析结果表明,文中提出的模型及求解算法与传统模型相比,有效地降低了综合能源系统的运行成本和碳排放量,提高了可再生能源的消纳能力。

电厂和政府行为策略演化博弈与仿真研究——基于农林生物质与煤耦合发电产业发展视角

“双碳”背景下,农林生物质与煤耦合发电成为煤电转型的新路径。政府如何制定有效的补贴和监管政策,以及电厂如何进行正确的策略选择是促进农林生物质与煤耦合发电产业发展的关键。通过构建政府和电厂的混合策略博弈模型,分析双方的博弈关系和行为策略动态演变过程,并运用系统动力学进行建模仿真,进一步探析关键因素对政府和电厂行为策略的影响路径。结果表明:政府和电厂的行为策略在较长时期里无法趋于稳定,而是在相互影响中波动变化。政府制定补贴和监管策略、提高耦合发电收益、降低耦合发电成本,都将促进更多电厂选择农林生物质与煤耦合发电,从而进一步促进产业发展。

面向新型电力系统的储能规划方法研究进展及展望

储能是新型电力系统非常重要的灵活性调节资源,在源网荷各端均可发挥重要的作用,在中国,储能的发展已经进入规模化发展期,如何合理、经济地利用好储能的关键是规划配置方法。在对储能规划方法研究现状的基础上,分析了储能投资运营主体多元化、应用场景和运行模式复杂化、储能技术多样化等新变化对储能规划方法的影响;提出了新能源聚集区考虑时空互补和共享机制的储能规划方法、电网侧充分市场竞争下的储能与输配电系统协同规划方法,以及用户侧电、热、氢多元储能合作/竞争共存下的规划方法。面向新型电力系统的储能规划,未来应注重电力系统不同发展阶段的整体协调性、储能投资运营主体多元化内生博弈机制的影响,以及规划方案在多目标多场景下的迁移学习方法。

考虑公众参与的循环经济监管模式构建及优化

中国提出发展循环经济已经近30年,取得可观成就的同时,面对“碳达峰”“碳中和”目标以及经济、社会高质量发展的要求,仍需有效的政策引导和监管机制推进循环经济进一步发展。构建包含公众参与的循环经济监管模式,将公众对政府审查机制和对企业上报机制的监督作用考虑在内,构建以政府审查、企业上报、公众监督为主要特征的演化博弈模型,并进一步构建系统动力学模型,分析公众舆论、政府激励、政府对企业的谎报惩罚等对均衡解的影响。结果表明:公众参与能够有效弥补政府监督的不足,同时制约企业和政府的行为选择,在成为循环经济最广泛的监督者的同时,实现政府、企业、公众的三方共赢。

基于三层博弈的社区综合能源系统电热交易策略

随着综合能源系统逐渐向智能化、清洁化、去中心化转型,发用电一体的产消者应运而生。为实现综合能源系统可再生能源的充分消纳,提高各主体的交互效益,提出基于三层博弈的社区综合能源系统电热交易策略。首先,建立基于社区合作博弈嵌套的综合能源运营商与能源社区主从博弈模型,运营商以最大化自身效益为目标制定分时电价、热价并传递给能源社区。能源社区响应运营商的电热决策,以消费剩余最大为目标制定与其他社区的交互策略,确定购能需求并传递给运营商。其次,为降低综合能源运营商碳排放,充分消纳各运营商的资源剩余,建立多综合能源运营商的纳什谈判模型。然后,利用Karush-Kuhn-Tucker(KKT)条件将模型进行转化,并利用McCormick法进行凸松弛。最后,采用交替方向乘子分布式算法对模型进行求解,通过算例验证了所提策略能够有效提升各主体交互效率、降低综合能源系统碳排放、提高各主体效益。

无人机集群对抗决策算法研究综述

无人机集群博弈对抗已经成为未来战争的发展趋势,无人机对抗决策算法的选择对提升无人机集群作战能力至关重要。本文深入探讨了基于规则的、基于博弈论的和基于神经网络的三大类无人机集群博弈对抗决策算法,并对它们的优势和局限性进行了全面分析与总结。在此基础上,提出将“基于多智能体强化学习的信用分配模型”和“基于角色的多智能体强化学习模型”应用于无人机集群博弈对抗的研究思路。最后,强调了选择适当的决策算法对于提高无人机集群作战效能的重要性,并为未来无人机对抗决策的发展提出了有益的建议,为相关领域的研究和应用提供了深入见解。

基于SD演化博弈的建筑工程质量潜在缺陷保险履约研究

当前,我国大力推行的住宅质量潜在缺陷保险(Inherent Defects Insurance,IDI)实施效果亟需改善。针对寻租行为导致的工程质量问题,基于保险公司视角构建履约阶段保险公司、承包商、风险管理机构的三方博弈模型,运用系统动力学进行仿真,改变合作损失、名誉损失、监督成本等数值,探究各主体行为演化过程及各因素对主体策略变化的影响。结果表明,保险公司积极监督受到承包商寻租和风险管理机构意向寻租策略的正向影响,出于长久合作考虑,不会出现寻租行为,监督成本是影响保险公司策略的主要因素。验证结果具有科学性,为IDI在市场中的顺利推行和应用提供了理论依据。