An Exploration of the Mechanism of Educational Scientific Decision-making in View of Bounded Rationality

The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientific decision-making of education policies.Therefore,based on this view and through shaping reasonable education policy values,this research gives full play to the driving force of educational scientific research on education policies and designs effective education decision-making information content and running agenda,thus optimizing the weigh principle of education policy proposals,advocating risk assessment and practice of education decisions,constructing institutional rationality of educational scientific decision-making,and finally realizing the rationality and scientificity of education policy decision-making.

Hierarchical Game Approach for Optimization of Regional Integrated Energy System Clusters Considering Bounded Rationality

Regional integrated energy system(RIES)cluster,i.e.,multi-source integration and multi-region coordination,is an effective approach for increasing energy utilization efficiency.The hierarchical architecture and limited information sharing of RIES cluster make it difficult for traditional game theory to accurately describe their game behavior.Thus,a hierarchical game approach considering bounded rationality is proposed in this paper to balance the interests of optimizing RIES cluster under privacy protection.A Stackelberg game with the cluster operator(CO)as the leader and multiple RIES as followers is developed to simultaneously optimize leader benefit and RIES utilization efficiency.Concurrently,a slight altruistic function is introduced to simulate the game behavior of each RIES agent on whether to cooperate or not.By introducing an evolutionary game based on bounded rationality in the lower layer,the flaw of the assumption that participants are completely rational can be avoided.Specially,for autonomous optimal dispatching,each RIES is treated as a prosumer,fexibly switching its market participation role to achieve cluster coordination optimization.Case studies on a RIES cluster verify effectiveness of the proposed approach.

Bounded Rationality Based Multi-VPP Trading in Local Energy Markets:A Dynamic Game Approach with Different Trading Targets

It is expected that multiple virtual power plants(multi-VPPs)will join and participate in the future local energy market(LEM).The trading behaviors of these VPPs needs to be carefully studied in order to maximize the benefits brought to the local energy market operator(LEMO)and each VPP.We propose a bounded rationality-based trading model of multiVPPs in the local energy market by using a dynamic game approach with different trading targets.Three types of power bidding models for VPPs are first set up with different trading targets.In the dynamic game process,VPPs can also improve the degree of rationality and then find the most suitable target for different requirements by evolutionary learning after considering the opponents’bidding strategies and its own clustered resources.LEMO would decide the electricity buying/selling price in the LEM.Furthermore,the proposed dynamic game model is solved by a hybrid method consisting of an improved particle swarm optimization(IPSO)algorithm and conventional largescale optimization.Finally,case studies are conducted to show the performance of the proposed model and solution approach,which may provide some insights for VPPs to participate in the LEM in real-world complex scenarios.

Computation of lower derivatives of rational triangular Bézier surfaces and their bounds estimation

By introducing the homogenous coordinates, degree elevation formulas and combinatorial identities, also by using multiplication of Bernstein polynomials and identity transformation on equations, this paper presents some explicit formulas of the first and second derivatives of rational triangular Bézier surface with respect to each variable (including the mixed derivative) and derives some estimations of bound both on the direction and magnitude of the corresponding derivatives. All the results above have value not only in surface theory but also in practice.

Computational Intelligence Determines Effective Rationality

Rationality is a fundamental concept in economics. Most researchers will accept that human beings are not fully rational. Herbert Simon suggested that we are ＂bounded rational＂. However, it is very difficult to quantify ＂bounded rationality＂, and therefore it is difficult to pinpoint its impact to all those economic theories that depend on the assumption of full rationality. Ariel Rubinstein proposed to model bounded rationality by explicitly specifying the decision makers＇ decision-making procedures. This paper takes a computational point of view to Rubinstein＇s approach. From a computational point of view, decision procedures can be encoded in algorithms and heuristics. We argue that, everything else being equal, the effective rationality of an agent is determined by its computational power - we refer to this as the computational intelligence determines effective rationality （CIDER） theory. This is not an attempt to propose a unifying definition of bounded rationality. It is merely a proposal of a computational point of view of bounded rationality. This way of interpreting bounded rationality enables us to （computationally） reason about economic systems when the full rationality assumption is relaxed.

The Rationality Dialogy Between Economics and Psychology

Economics and psychology take distinct approaches to predicting and formalizing human behavior. Economics focuses on the normative view of rationality, while psychology emphasizes the descriptive nature of rationality. This article reviews models of rationality related to understanding human decision making, including notions of complete rationality, bounded rationality, and ecological rationality. By examining the aims and functions of such rationality models, the author wishes to draw attention to the utility of ecological rationality and adaptive rationality approaches in a unified theoretical model for understanding human rationality. The ecological rationality approach evaluates not only by performance, but more importantly by how well the behavior fits the individual' s environment. The adaptive rationality approach completes this model by additionally incorporating changes to the environment.

基于认知层级视角的供应链成员定价决策分析

供应链成员的决策受到决策者行为特性的影响.本研究以一个供应商和一个零售商组成的供应链系统为研究对象,实施管理实验探究供应链成员定价决策行为.分别以认知层级模型、有限理性模型,以及认知层级与有限理性结合的综合模型刻画决策者行为,并对比分析三种模型的似然估计结果,得出综合模型能够更好地解读供应链成员的定价决策行为,揭示了决策者定价行为偏离理论决策最优的主要原因是决策者对其他决策者战略能力推理水平的不一致性信念,以及无法对其他决策者决策做出最优反应的决策偏差.同时,决策者的认知层级受到其决策顺序的影响.相对于先行动者可以获得的信息,由于后行动者可以接收到先行者的决策信息,所以后行动者的认知层级较高.

有限理性决策理论下驾驶信息过载研究及应用

随着汽车网联化和智能化的发展,汽车驾驶过程面临着车内外多源信息过载的影响,这可能会产生交通安全问题.驾驶信息过载包含感知、认知和决策等复杂神经机制.在知识、时间和精力有限的情况下,当驾驶员处于庞大、繁杂、多变环境中排查信息对象并进行决策时,决策都是在有限度的理性条件下进行,且常带有主观因素,这是有限理性决策理论的基本原理.汽车工业界基于有限理性决策理论,根据人的特性研究了AR-HUD控制驾驶信息过载的汽车驾驶辅助技术以及OLED车载显示的应用,驾驶员在面临信息过载时可快速筛选关键信息,做出正确驾驶决策,以此来提升驾驶的安全性.本文通过综述国内外学者在驾驶信息过载原因、生理心理机制以及控制驾驶信息过载的技术和装备等方面的研究成果,为安全驾驶、汽车智能化发展的产学研结合提供参考.

大数据背景下点击合同不正当格式条款的规制路径探析

以我国15个网络平台的用户协议和隐私政策为例进行实证分析,归纳出点击合同不正当格式条款包括单方变更权条款、自动化决策条款、无限制用户内容授权条款等,现有的显失公平、提示说明义务、自动化决策规范等手段虽然能够提供救济,但都因其自身缺憾而无法充分解决问题,使点击合同不正当格式条款的规制仍存有疏缺。因此,有必要通过设置格式条款负面清单、加强动态化监管、优化平台提示说明义务、设置脱离自动化决策权选项、明确告知义务范围、提高用户注意意识等手段为网络环境下用户的各项权益保驾护航。

有限理性视域下的职务犯罪调查决策研究

职务犯罪调查过程中需要作出一系列决策,这些决策是在有限理性的框架下做出的。职务犯罪调查作为一项认识活动,存在着特定的认识路径,并伴随着趋避冲突、双趋冲突、双避冲突、多重趋避冲突等目标冲突,调查决策中所面临的不确定性正是有限理性的具体体现。在有限理性的视域下,可从建立专家智库、开展案例讲评、发挥联动优势、用好大数据手段等方面提高职务犯罪调查决策的质量。

考虑电动汽车用户有限理性的定制化电价套餐设计

考虑到售电公司对提高市场占有率和收益的需求,电动汽车用户对经济和舒适的追求,以及电动汽车保有量基数大且还在持续快速上升的情况,提出了一种考虑电动汽车用户有限理性的定制化电价套餐设计方法。首先,利用蒙特卡洛方法模拟生成一些电动汽车用户的充电需求以增加充电负荷数据,并采用k-medoids聚类算法对电动汽车用户按其充电负荷聚类出典型电动汽车用户的充电需求曲线。然后,通过熵权法计算电动汽车用户效用,并在此基础上应用演化博弈论分析电动汽车用户在有限理性情况下的电价套餐选择情况。最后,建立考虑电动汽车用户有限理性的电价套餐双层优化模型,上层模型优化目标为售电公司购售电收益最大,下层模型优化目标为电动汽车用户效用最大。算例结果表明该定制化电价套餐不但能够有效地提高售电公司的营业利润,而且能够降低用户用电成本。

考虑不同救援能力的应急救援人员派遣演化博弈

为解决突发事件初期救援人员的供需不平衡问题,提出构建突发事件应急救援人员派遣的演化博弈模型.综合考虑突发事件和次生灾害对救援网络道路的破坏,以及有限理性的受灾群众对救援人员派遣存在的竞争心理因素,从受灾群众视角,分析多个受灾点种群对救援人员派遣的博弈问题,利用复制者动态方程模拟各受灾点对救援人员派遣策略选择的动态演化过程,构建具有多个救援点和多个受灾点的多阶段救援人员派遣模型,并通过算例分析各受灾点救援人员派遣的动态演化过程和最佳方案.结果表明,利用综合考虑应急救援过程的多阶段动态特性和受灾点间的有限理性博弈心理模型,求解救援派遣方案是实用且可行的.参数敏感性分析结果给出了分别适用于3种不同救援场景的派遣方案.研究成果可为突发事件应急救援人员的派遣决策提供参考依据.

有限理性条件下多层次轨道交通客流拥堵传播机理研究

多层次轨道交通系统通过融合不同制式轨道交通,实现了运输能力的灵活配置和互补,但也增加了客流拥堵传播的不确定性,极易出现客流拥堵的跨层级传播。在分析乘客出行有限理性选择行为的基础上,通过引入心理账户理论,建立了广义出行时间账户和拥堵程度账户,并利用改进的价值函数与决策权重函数,刻画了乘客出行路径的综合交易效用。通过考虑出行方式与出行路径双因素,建立了基于巢式Logit-心理账户-累积前景理论(Nested Logit-mental Accountingcumulative Prospect Theory, NL-MA-CPT)的乘客出行方式选择预测模型。在此基础上,通过引入改进的易感-感染-恢复(Upgraded Susceptible-infected-recovered, USIR)模型,提出了考虑乘客选择行为的多层次轨道交通客流拥堵传播模型,并刻画了有限理性条件下的传播速率和恢复速率。最后,以北京市多层次轨道交通为例,验证模型的有效性,并通过灵敏度分析,揭示相关关键因素对拥堵传播的影响机理。研究结果表明:多层次轨道交通网络客流拥堵传播具有显著的波动性和收敛性特征,而传播速率和恢复速率直接影响拥堵传播的强度及影响范围,且随着网络层数的增加,乘客出行选择决策的有限理性特征对拥堵传播的影响更加显著。本研究可为运营企业制定客流拥堵控制策略提供一定的理论参考依据。

数字化转型与股票误定价:抑制还是助推

以沪深A股上市公司为研究样本,探讨数字化转型对股票误定价的影响及其机制。研究结果发现,数字化转型显著推高了股票误定价,且主要表现为股价高估。机制检验表明,数字化转型会吸引投资者和分析师关注,提高投资者乐观情绪,从而加剧股票误定价。异质性分析发现,融资融券交易和高质量的会计信息能够缓解数字化转型对股票误定价的影响,而市场情绪高涨期间数字化转型对股票误定价的影响更显著。建议有关部门进一步健全上市公司信息披露制度,加强对数字化转型信息披露的监管,以缓解数字化转型对股票误定价的影响。

基于前景理论的违法停车行为分析——以北京市为例

违法停车是交通政策中应涉及的,而驾驶员在停车时是否选择违法停车的决策过程是有限理性的。通过调查发现驾驶员最关注步行时间,其次考虑停车费率和巡查频率;对停车费率、巡查频率的关注程度,随着年龄或者收入的增加呈现递减趋势,而对步行时间的重视程度,随着年龄或者收入的增加呈现递减趋势;基于前景理论建立的违法停车选择模型发现:低年收入群体对停车费率、罚款额、被罚概率的敏感度相对较高,而高收入群体对三者的敏感度相对较低。

Formulation and solution for calibrating boundedly rational activity-travel assignment:An exploratory study

Parameter calibration of the traffic assignment models is vital to travel demand analysis and management.As an extension of the conventional traffic assignment,boundedly rational activity-travel assignment(BR-ATA)combines activity-based modeling and traffic assignment endogenously and can capture the interdependencies between high dimensional choice facets along the activity-travel patterns.The inclusion of multiple episodes of activity participation and bounded rationality behavior enlarges the choice space and poses a challenge for calibrating the BR-ATA models.In virtue of the multi-state supernetwork,this exploratory study formulates the BRATA calibration as an optimization problem and analyzes the influence of the two additional components on the calibration problem.Considering the temporal dimension,we also propose a dynamic formulation of the BR-ATA calibration problem.The simultaneous perturbation stochastic approximation algorithm is adopted to solve the proposed calibration problems.Numerical examples are presented to calibrate the activity-based travel demand for illustrations.The results demonstrate the feasibility of the solution method and show that the parameter characterizing the bounded rationality behavior has a significant effect on the convergence of the calibration solutions.

全局求解线性比式和问题的迭代算法

本文针对一类线性比式和问题(SLR)提出一种迭代算法.首先将问题(SLR)转化为等价问题,然后通过提出的松弛技术将等价问题松弛为线性规划问题,并利用区域缩减技术加速算法的迭代.最后给出算法的收敛性以及复杂度,数值实验表明了算法的有效性.

计及有限理性的多微电网电能交易策略

多微电网在电能交易时会出现有限理性行为,具体表现为对损失、不确定性以及长短期收益具有不同的偏好。基于时间偏好理论和前景理论提出了计及有限理性的多微电网电能交易策略。多微电网运营商作为领导者,以所有微电网收益最大为目标,确定微电网之间的交易电价来激励微电网间的合作交易。微电网作为追随者,在保障自身时间偏好前景值最大的前提下制定交易策略。算例分析表明:该策略可快速确定微电网之间的交易电价,有效提高微电网整体收益和DG(分布式电源)利用率。

有限理性视域下的女性出走——以丁玲的《梦珂》为例

《梦珂》是丁玲初入文坛的第一部短篇小说,代表了丁玲初期创作的总主题——五四落潮后女性追求独立的反叛精神与社会现实的矛盾冲突。小说中梦珂经历了三次出走,非但没有看到希望,反而在一次次逃离中走向深渊。从有限理性视角出发,探究梦珂三次抉择所造成的憧憬和失落,可以为理解特定时代背景下女性的生存困境和作家的创作转型提供新角度。