北京市大型医院空间优化与再配置的计算实验研究

医疗资源的合理布局是构建高质量医疗体系的重要基础。随着北京疏解工作的全面启动,以往高度集中布局的北京医疗资源需要重新配置。如何实现优质医疗资源空间布局的优化,既要解决“看病难、看病贵”,还不能加剧北京的“大城市病”,这是疏解面临的新课题。研究以计算社会科学的方法为基础,北京医疗资源疏解为背景,开发基于agent的城市医疗资源空间配置和布局的计算实验平台,讨论“点轴放射”模式和“组团”模式等不同布局情景下居民的居住选择和就医行为,“动态”观察和评估不同模式在平常和应急两种状态下资源配置的合理性和有效性。计算实验结果表明,“点轴放射”模式的医院布局在空间分布上更加均匀,能够随着人口的迁移互动逐渐形成自己的服务半径,效果略好于“组团”模式。然而,在灾情疫情等应急情形下,“组团”模式的医疗资源配置表现要显著好于“点轴放射”模式。研究表明,基于agent的建模和计算实验方法能够为利用真实数据建立现实模型展开这类布局事前研究和规划提供坚实的基础。

Agent-based simulation of alternative classroom evacuation scenarios

Due to the growing number of emergency accidents occurring around students, evacuation issues have become significantly important for both school officials and architects. Simply following construction codes cannot ensure that a building＇s layout is suitable for evacuation behaviors; therefore, to discover the suitable planning schemes, we have introduced an agentbased simulation model via Netlogo to investigate the interrelationships between evacuation efficiency and classroom layouts. Before conducting modeling experiments, both the simulation structure and the sensitivity to its parameter settings are examined by validation research and sensitivity analysis. Furthermore, to demonstrate the importance of conducting fire drills with students, two different types of behavior rules are designed to reflect the distinctive characteristics of students evacuating without instructions and students evacuating in good order. The general comparison results show us that the classroom layout with two exits shortens students＇ evacuation time, and the premeditated behavior rules, meaning that students who follow preset instructions to arrange their activities, not only escape faster but also have some advantages in ensuring their safety during the evacuation process. Moreover, at the end of this paper, several methods of improving this simulation model are proposed for more complex research in the future.

Agent-based modeling in urban and architectura research： A brief literature review

Agent-based modeling （ABM） is an emerging modeling approach. In the past two decades, agent-based models have been increasingly adapted by social scientists, especially scientists in urban and geospatial studies, as an effective paradigm for framing the underlying problems of complex and dynamic processes. As a result, the literature of ABM research is growing rapidly, covering a diverse range of topics. This paper presents a systematic literature review of ABM research, and discusses both theoretical issues such as ABM definition and architecture, and practical issues such as ABM applications and development platforms. A comprehensive and up-to-date bibliography is presented.

Agent-based Modeling and Simulation for the Electricity Market with Residential Demand Response

Currently,critical peak load caused by residential customers has attracted utility companies and policymakers to pay more attention to residential demand response(RDR)programs.In typical RDR programs,residential customers react to the price or incentive-based signals,but the actions can fall behind flexible market situations.For those residential customers equipped with smart meters,they may contribute more DR loads if they can participate in DR events in a proactive way.In this paper,we propose a comprehensive market framework in which residential customers can provide proactive RDR actions in a day-ahead market(DAM).We model and evaluate the interactions between generation companies(GenCos),retailers,residential customers,and the independent system operator(ISO)via an agent-based modeling and simulation(ABMS)approach.The simulation framework contains two main procedures—the bottom-up modeling procedure and the reinforcement learning(RL)procedure.The bottom-up modeling procedure models the residential load profiles separately by household types to capture the RDR potential differences in advance so that residential customers may rationally provide automatic DR actions.Retailers and GenCos optimize their bidding strategies via the RL procedure.The modified optimization approach in this procedure can prevent the training results from falling into local optimum solutions.The ISO clears the DAM to maximize social welfare via Karush-Kuhn-Tucker(KKT)conditions.Based on realistic residential data in China,the proposed models and methods are verified and compared in a large multi-scenario test case with 30,000 residential households.Results show that proactive RDR programs and interactions between market entities may yield significant benefits for both the supply and demand sides.The models and methods in this paper may be used by utility companies,electricity retailers,market operators,and policy makers to evaluate the consequences of a proactive RDR and the interactions among multi-entities.

A multilevel and dynamic model of intragroup conflict and decision making:application of agent-based modeling

Although intragroup conflict has both multilevel and dynamic natures,less attention has been paid to establishing a holistic model of intragroup conflict that emerges across levels and unfolds over time.To address this research gap,we extend the multilevel view of intragroup conflict(Korsgaard et al.2008)to develop a multilevel and dynamic model of intragroup conflict that explicitly includes(1)the role of time and(2)the feedback loop to encompass the dynamic aspect of intragroup conflict.We further instantiate the extended model in the context of team decision-making.To achieve this and systematically examine the complex relationships,we use agentbased modeling and simulation(ABMS).We directly investigate how two types of intragroup conflict—task and relationship conflict—interplay with cross-level antecedences,interrelate and develop over time,and affect team outcomes.This study adds to the intragroup conflict research by extending the field with multilevel and dynamic views.

Agent行为建模与仿真研究的热点与趋势——基于CiteSpace图谱量化分析

目的:比较国内外Agent行为建模与仿真研究热点与趋势,为我国研究者更有效地应用Agent行为建模与仿真提供参考依据。方法:运用CiteSpace5.7R5软件对中国知网和Web of Science核心合集数据库2011年1月1日至2021年3月31日中有关Agent行为建模与仿真研究的文献进行图谱量化分析。结果:共检索到有效中文文献864篇、英文文献2323篇,国内发文量整体呈下降趋势,国外发文量整体呈上升趋势,发文量高的国家集中在发达国家,国外研究前沿已经延伸到物理学、金融学、哲学、生物学、物流学、人工智能等方面。国内研究热点主要集中在社会学、物理学、网络模型等方面。结论:Agent行为建模与仿真研究的应用范围较广泛,与国际相比国内Agent行为建模与仿真研究还存在一定的差距,研究深度和广度有待进一步拓展,国内应参考国际Agent行为建模与仿真研究的热点及前沿,探索适合我国特色的Agent行为建模与仿真系统体系,以促进我国Agent行为建模与仿真的发展。

Complexity Science and Cyber Operations: A Literature Survey

Complexity science is an interdisciplinary scientific field that analyzes systems as holistic entities consisting of characteristics beyond the sum of a system’s individual elements.This paper presents current research across the literature promoting cyber security as a complex adaptive system.We introduce complex systems concepts and fields of study,and deliver historical context,main themes,and current research relevant to cyber operations.Examples of cyber operations research leveraging agent-based modeling demonstrate the power of computational modeling grounded in complex systems principles.We discuss cyber operations as a scientific field,define current shortfalls for scientific rigor,and provide examples of how a complexity science foundation can further research and practice across a variety of cyber-based efforts.We propose standard definitions applicable to complex systems for cyber professionals and conclude with recommendations for future cyber operations research.

基于Swarm的股权拍卖机制设计与仿真研究

基于多主体的建模仿真方法,运用particle swarm optimization(PSO)群体智能算法模拟信息交互条件下外部投资者估价变化的学习机制和演化规律,在机制设计的基础上,建立了实现风险投资退出的股权拍卖模型.在Swarm平台上对股权拍卖模型的仿真分析表明,所设计的股权拍卖机制能够显著地提高风险投资家的收益,并能帮助风险投资家预测外部投资者的估价和拍卖参与度的变化.对股权拍卖模型的参数仿真发现,风险投资家可以通过引入更多的外部投资者参与股权拍卖来进一步提高自己的收益;即便外部投资者过度强化单一学习能力,最终也可以得到相对理想的股权拍卖结果.本文的研究可以为风险投资家的策略选择提供参考依据.