In this paper,we combine an agent-based model of multi-asset stock market with circuit breaker mechanism and empirical analysis of S&P 500 Index to study market behaviors under the circuit breaker.The artificial s...In this paper,we combine an agent-based model of multi-asset stock market with circuit breaker mechanism and empirical analysis of S&P 500 Index to study market behaviors under the circuit breaker.The artificial stock market model can reproduce the stylized fact that the stock index triggers a circuit breaker.The results show that the smaller the circuit breaker,the more likely the circuit breaker events will occur.And the higher the traders'index-dependent strength,the more likely the circuit breaker events will occur.From the perspective of market behaviors under the stock index circuit breaker,we find that the market volatility,the correlation of individual stock returns and the convergence of traders'behavior on the circuit breaker day are higher than those before the circuit breaker day when the circuit breaker in the market is set relatively small or traders refer to the stock index more for decision-making.This is because the smaller circuit breaker mechanism and traders'more reference to the stock index for decision-making make the behavior of originally heterogeneous traders in the market converge,which aggravates the occurrence ofcircuitbreakers.展开更多
The purpose of this paper is to generalize Landscape theory proposed by R. Axelrod and, then, to apply it to the civil aviation industry for simulating alliance formations in it. Landscape theory provides a well-known...The purpose of this paper is to generalize Landscape theory proposed by R. Axelrod and, then, to apply it to the civil aviation industry for simulating alliance formations in it. Landscape theory provides a well-known agent-based simulation model for analyzing alliance (or coalition) formation process. When a set N of agents or autonomous decision makers is given, the theory assumes that each agent tries to make a coalition in such a way that the resulting alliance minimizes its frustration. The theory is essentially based on two premises. One is that a propensity is symmetric, i.e., the propensity of agent i toward j is exactly the same as that of j toward i for any agents i and j in N. The other is that the number of alliances is restricted to two, i.e., at any moment N is partitioned into two parties. Though the two basic premises underpin the theory and make the model simple and operational, they do not always reflect alliance formation processes in a realistic way. A generalized Landscape theory that this paper proposes removes them and allows asymmetric propensity and existence of alliances of any number. Since the premises are essential for the model, the generalization requires a drastic reconstruction of the whole idea of the theory. Finally, we analyze a real alliance formation process in the civil aviation industry. This analysis provides interesting insights about the industry as well as some validation of our generalized Landscape theory.展开更多
This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionar...This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionary processes.By representing agents and their defined environments with probabilistic interactions,ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level.The review looks into the applications of ABM in portraying some of the key components of emotions and cognition-empathy,cooperation,decision making,and emotional transmission-and analyzes the problems including scalability,empirical validation,and description of sensitive emotional states.The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence(AI)techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli.This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology,neuroscience,and engineering.This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking,healthcare,and education.展开更多
Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subs...Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.展开更多
There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken com...There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken communities have been gaining momentum.As the community resilience analysis aims to guide how to lay out effective hazard mitigation strategies to decrease damage and improve recovery,a comprehensive and accurate approach is necessary.Agent-based modeling,an analysis approach in which different types of agents are created with their properties and behavior clearly defined to simulate the processes of those agents in an external environ-ment,is the most comprehensive and accurate approach so far to conducting community resilience simulations and investigating the decision-making for mitigation and recovery under natural hazards.In this paper,agent-based models(ABMs)are created to simulate the recovery process of a virtual testbed based on the real-world community in Joplin City,MO.The tornado path associated with the real-world tornado event that occurred in May 2011 is adopted in the tornado hazard modeling for the Joplin testbed.In addition,agent-based models are created for another virtual community in the Midwest United States named Centerville using an assumed tornado scenario of the same EF-scale as that in Joplin.The effects of hazard mitigation strategies on the two communities are also explored.A comparison between the analysis results of these two testbeds can indicate the influence of the characteristics of a tornado-prone community on the resilience of the community as well as on the effects of hazard mitigation strategies.It is observed that a community’s level of development significantly impacts the tornado resilience.In addition,the effects of a specific type of hazard mitigation strategy on the recovery process are contingent upon testbed characteristics.展开更多
A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions.The effect of the hazard geomet...A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions.The effect of the hazard geometry(center and angle of tornado path as well as the tornado width)is studied herein on how it influences the recovery of physical and social systems within the community.Given that pre-disaster preparedness including mitigation strategies(e.g.,retrofits)and policies(e.g.,insurance)is crucial for increasing the resilience of the community and facilitating a faster recovery process,in this study,the impact of various mitigation strategies and policies on the recovery trajectory and resilience of a typical US community subjected to a tornado is investigated considering different sources of uncertainties.The virtual testbed of Centerville is selected in this paper and is modeled by adopting the Agent-based modeling(ABM)approach which is a powerful tool for conducting community resilience analysis that simulates the behavior of different types of agents and their interactions to capture their interdependencies.The results are presented in the form of recovery time series as well as calculated resilience indices for various community systems(lifeline networks,schools,healthcare,businesses,and households).The results of this study can help deepen our understanding of how to efficiently expedite the recovery process of a community.展开更多
Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises.This study developed a universal dynamic agent-based supply cha...Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises.This study developed a universal dynamic agent-based supply chain model to achieve tradeoffs between environmental risk reduction and economic sus-tainability.The model was used to conduct high-resolution daily simulations of the dynamic shifts in enterprise operations and their cascading effects on supply chain networks.It includes production,con-sumption,and transportation agents,attributing economic features to supply chain components and cap-turing their interactions.It also accounts for adaptive responses to daily external shocks and replicates realistic firm behaviors.By coupling high spatial-temporal resolution firm-level data from 18916 chemical enterprises,this study investigates the economic and environmental impacts of an environmen-tal policy resulting in the closure of 1800 chemical enterprises over three years.The results revealed a significant economic loss of 25.8 billion USD,ranging from 23.8 billion to 31.8 billion USD.Notably,over 80%of this loss was attributed to supply chain propagation.Counterfactual analyses indicated that imple-menting a staggered shutdown strategy prevented 18.8%of supply chain losses,highlighting the impor-tance of a gradual policy implementation to prevent abrupt supply chain disruptions.Furthermore,the study highlights the effectiveness of a multi-objective policy design in reducing economic losses(about 29%)and environmental risks(about 40%),substantially enhancing the efficiency of the environmental policy.The high-resolution simulations provide valuable insights for policy designers to formulate strategies with staggered implementation and multiple objectives to mitigate supply chain losses and environmental risks and ensure a sustainable future.展开更多
This paper proposes a novel agent-based model combining private information diffusion to explain time-series momentum and reversal.Private information transmission allows heterogeneous trading strategies coexist in th...This paper proposes a novel agent-based model combining private information diffusion to explain time-series momentum and reversal.Private information transmission allows heterogeneous trading strategies coexist in the artificial market.The experiments reproduce momentum in short horizon and reversal in long horizon in the artificial financial market.Moreover,the authors also analyze how the private information contagion affects the momentum.Meanwhile,the authors find the significant price trend and excess volatility of volume when private information diffuses gradually.展开更多
BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidec...BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.展开更多
The volume of instant delivery has witnessed a significant growth in recent years.Given the involvement of numerous heterogeneous stakeholders,instant delivery operations are inherently characterized by dynamics and u...The volume of instant delivery has witnessed a significant growth in recent years.Given the involvement of numerous heterogeneous stakeholders,instant delivery operations are inherently characterized by dynamics and uncertainties.This study introduces two order dispatching strategies,namely task buffering and dynamic batching,as potential solutions to address these challenges.The task buffering strategy aims to optimize the assignment timing of orders to couriers,thereby mitigating demand uncertainties.On the other hand,the dynamic batching strategy focuses on alleviating delivery pressure by assigning orders to couriers based on their residual capacity and extra delivery dis tances.To model the instant delivery problem and evaluate the performances of order dis patching strategies,Adaptive Agent-Based Order Dispatching(ABOD)approach is developed,which combines agent-based modelling,deep reinforcement learning,and the Kuhn-Munkres algorithm.The ABOD effectively captures the system’s uncertainties and heterogeneity,facilitating stakeholders learning in novel scenarios and enabling adap tive task buffering and dynamic batching decision-makings.The efficacy of the ABOD approach is verified through both synthetic and real-world case studies.Experimental results demonstrate that implementing the ABOD approach can lead to a significant increase in customer satisfaction,up to 275.42%,while simultaneously reducing the deliv ery distance by 11.38%compared to baseline policies.Additionally,the ABOD approach exhibits the ability to adaptively adjust buffering times to maintain high levels of customer satisfaction across various demand scenarios.As a result,this approach offers valuable sup port to logistics providers in making informed decisions regarding order dispatching in instant delivery operations.展开更多
The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are havi...The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.展开更多
Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems.As a process-oriented modelling approach,agent based model(ABM)plays an important role in reveali...Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems.As a process-oriented modelling approach,agent based model(ABM)plays an important role in revealing the driving forces of land change and understanding the process of land change.This paper starts from three aspects:The theory,application and modeling framework of ABM.First,we summarize the theoretical basis of ABM and introduce some related concepts.Then we expound the application and development of ABM in both urban land systems and agricultural land systems,and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region,China.On the basis of combing the ABM modeling protocol,we propose the land system ABM modeling framework and process from the perspective of agents.In terms of urban land use,ABM research initially focused on the study of urban expansion based on landscape,then expanded to issues like urban residential separation,planning and zoning,ecological functions,etc.In terms of agricultural land use,ABM application presents more diverse and individualized features.Research topics include farmers’behavior,farmers’decision-making,planting systems,agricultural policy,etc.Compared to traditional models,ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data.However,due to its unique bottom-up model structure,ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.展开更多
Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant＇s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the ter- ritory that they patr...Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant＇s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the ter- ritory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when： 1） there is a mismatch in nest- mate recognition cues and 2） each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin （5-HT） and octopamine （OA） modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and ag- gression. In this article, we develop and explore an agent-based model that conceptualizes how in- dividual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based de- cision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.展开更多
This work re-examined the simulation result of game analysis (Joshi et al., 2000) based on an agent-based model, Santa Fe Institute Artificial Stock Market. Allowing for recent research work on this artificial model, ...This work re-examined the simulation result of game analysis (Joshi et al., 2000) based on an agent-based model, Santa Fe Institute Artificial Stock Market. Allowing for recent research work on this artificial model, this paper’s modified game simulations found that the dividend amplitude parameter is a crucial factor and that the original conclusion still holds in a not long period, but only when the dividend amplitude is large enough. Our explanation of this result is that the dividend amplitude pa- rameter is a measurement of market uncertainty. The greater the uncertainty, the greater the price volatility, and so is the risk of investing in the stock market. The greater the risk, the greater the advantage of including technical rules.展开更多
Fraudulent actions of a trader or a group of traders can cause substantial disturbance to the market,both directly influencing the price of an asset or indirectly by misin-forming other market participants.Such behavi...Fraudulent actions of a trader or a group of traders can cause substantial disturbance to the market,both directly influencing the price of an asset or indirectly by misin-forming other market participants.Such behavior can be a source of systemic risk and increasing distrust for the market participants,consequences that call for viable countermeasures.Building on the foundations provided by the extant literature,this study aims to design an agent-based market model capable of reproducing the behavior of the Bitcoin market during the time of an alleged Bitcoin price manipulation that occurred between 2017 and early 2018.The model includes the mechanisms of a limit order book market and several agents associated with different trading strategies,including a fraudulent agent,initialized from empirical data and who performs market manipulation.The model is validated with respect to the Bitcoin price as well as the amount of Bitcoins obtained by the fraudulent agent and the traded volume.Simulation results provide a satisfactory fit to historical data.Several price dips and volume anomalies are explained by the actions of the fraudulent trader,completing the known body of evidence extracted from blockchain activity.The model suggests that the presence of the fraudulent agent was essential to obtain Bitcoin price development in the given time period;without this agent,it would have been very unlikely that the price had reached the heights as it did in late 2017.The insights gained from the model,especially the connection between liquidity and manipulation efficiency,unfold a discussion on how to prevent illicit behavior.展开更多
Ulcerative colitis, an inflammatory bowel disease, is a chronic inflammatory disorder that results in ulcers of the colon and rectum without known etiology. Ulcerative colitis causes a huge public health care burden p...Ulcerative colitis, an inflammatory bowel disease, is a chronic inflammatory disorder that results in ulcers of the colon and rectum without known etiology. Ulcerative colitis causes a huge public health care burden particularly in developed countries. Many studies suggest that ulcerative colitis results from an abnormal immune response against components of cornrnensal rnicrobiota in genetically susceptible individuals. However, understanding of the disease mechanisms at cellular and molecular levels remains largely elusive. In this paper, a network model is developed based on our previous study and computer simulations are perforrned using an agent-based network modeling to elucidate the dynamics of immune response in ulcerative colitis progression. Our modeling study identifies several important positive feedback loops as a driving force for ulcerative colitis initiation and progression. The results demonstrate that although immune response in ulcerative colitis patients is dominated by anti-inflarnrnatory/regulatory cells such as alternatively activated rnacrophages and type II natural killer T cells, proinflarnrnatory cells including classically activated rnacrophages, T helper 1 and T helper 17 cells, and their secreted cytokines tumor necrosis factor-α, interleukin-12, interleukin-23, interleukin-17 and interferon-γ remain at certain levels （lower than those in Crohn＇s disease, another inflammatory bowel disease）. Long-terrn exposure to these proinflarnrnatory components, causes rnucosal tissue damage persistently, leading to ulcerative colitis. Our simulation results are qualitatively in agreement with clinical and laboratory measurements, offering novel insight into the disease mechanisms.展开更多
Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(...Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.展开更多
Agent-based models (ABMs) are capable of constructing individual system components at different levels of representation to describe non-linear relationships between those components. Compared to a traditional mathema...Agent-based models (ABMs) are capable of constructing individual system components at different levels of representation to describe non-linear relationships between those components. Compared to a traditional mathematical modeling approach, agent-based models have an inherent spatial component with which they can easily describe local interactions and environmental heterogeneity. Furthermore, agent-based model maps interactions among agents inherently to the biological phenomenon by embedding the stochastic nature and dynamics transitions, thereby demonstrating suitability for the development of complex biological processes. Recently, an abundance of literature has presented application of agent-based modeling in the biological system. This review focuses on application of agent-based modeling to progression in simulation of infectious disease in the human immune system and discusses advantages and disadvantages of agent-based modeling application. Finally, potential implementation of agent-based modeling in relation to infectious disease modeling in future research is explored.展开更多
基金supported by the Beijing Municipal Social Science Foundation under Grant No.22JCC111.
文摘In this paper,we combine an agent-based model of multi-asset stock market with circuit breaker mechanism and empirical analysis of S&P 500 Index to study market behaviors under the circuit breaker.The artificial stock market model can reproduce the stylized fact that the stock index triggers a circuit breaker.The results show that the smaller the circuit breaker,the more likely the circuit breaker events will occur.And the higher the traders'index-dependent strength,the more likely the circuit breaker events will occur.From the perspective of market behaviors under the stock index circuit breaker,we find that the market volatility,the correlation of individual stock returns and the convergence of traders'behavior on the circuit breaker day are higher than those before the circuit breaker day when the circuit breaker in the market is set relatively small or traders refer to the stock index more for decision-making.This is because the smaller circuit breaker mechanism and traders'more reference to the stock index for decision-making make the behavior of originally heterogeneous traders in the market converge,which aggravates the occurrence ofcircuitbreakers.
文摘The purpose of this paper is to generalize Landscape theory proposed by R. Axelrod and, then, to apply it to the civil aviation industry for simulating alliance formations in it. Landscape theory provides a well-known agent-based simulation model for analyzing alliance (or coalition) formation process. When a set N of agents or autonomous decision makers is given, the theory assumes that each agent tries to make a coalition in such a way that the resulting alliance minimizes its frustration. The theory is essentially based on two premises. One is that a propensity is symmetric, i.e., the propensity of agent i toward j is exactly the same as that of j toward i for any agents i and j in N. The other is that the number of alliances is restricted to two, i.e., at any moment N is partitioned into two parties. Though the two basic premises underpin the theory and make the model simple and operational, they do not always reflect alliance formation processes in a realistic way. A generalized Landscape theory that this paper proposes removes them and allows asymmetric propensity and existence of alliances of any number. Since the premises are essential for the model, the generalization requires a drastic reconstruction of the whole idea of the theory. Finally, we analyze a real alliance formation process in the civil aviation industry. This analysis provides interesting insights about the industry as well as some validation of our generalized Landscape theory.
文摘This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionary processes.By representing agents and their defined environments with probabilistic interactions,ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level.The review looks into the applications of ABM in portraying some of the key components of emotions and cognition-empathy,cooperation,decision making,and emotional transmission-and analyzes the problems including scalability,empirical validation,and description of sensitive emotional states.The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence(AI)techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli.This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology,neuroscience,and engineering.This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking,healthcare,and education.
基金supported by National Natural Science Foundation of China(72288101,72361137002,and 72101018)the Dutch Research Council(NWO Grant 482.22.01).
文摘Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.
基金Financial support for this work was provided by the US Department of Commerce,the National Institute of Standards and Technology(NIST)under the Financial Assistance Award Number#70NANB20H008the US National Science Foundation(NSF)under Award Number 2052930.
文摘There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken communities have been gaining momentum.As the community resilience analysis aims to guide how to lay out effective hazard mitigation strategies to decrease damage and improve recovery,a comprehensive and accurate approach is necessary.Agent-based modeling,an analysis approach in which different types of agents are created with their properties and behavior clearly defined to simulate the processes of those agents in an external environ-ment,is the most comprehensive and accurate approach so far to conducting community resilience simulations and investigating the decision-making for mitigation and recovery under natural hazards.In this paper,agent-based models(ABMs)are created to simulate the recovery process of a virtual testbed based on the real-world community in Joplin City,MO.The tornado path associated with the real-world tornado event that occurred in May 2011 is adopted in the tornado hazard modeling for the Joplin testbed.In addition,agent-based models are created for another virtual community in the Midwest United States named Centerville using an assumed tornado scenario of the same EF-scale as that in Joplin.The effects of hazard mitigation strategies on the two communities are also explored.A comparison between the analysis results of these two testbeds can indicate the influence of the characteristics of a tornado-prone community on the resilience of the community as well as on the effects of hazard mitigation strategies.It is observed that a community’s level of development significantly impacts the tornado resilience.In addition,the effects of a specific type of hazard mitigation strategy on the recovery process are contingent upon testbed characteristics.
基金Financial support for this work was provided by the US Department of Commerce,National Institute of Standards and Technology(NIST)under the Financial Assistance Award Number(FAIN)#70NANB20H008.
文摘A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions.The effect of the hazard geometry(center and angle of tornado path as well as the tornado width)is studied herein on how it influences the recovery of physical and social systems within the community.Given that pre-disaster preparedness including mitigation strategies(e.g.,retrofits)and policies(e.g.,insurance)is crucial for increasing the resilience of the community and facilitating a faster recovery process,in this study,the impact of various mitigation strategies and policies on the recovery trajectory and resilience of a typical US community subjected to a tornado is investigated considering different sources of uncertainties.The virtual testbed of Centerville is selected in this paper and is modeled by adopting the Agent-based modeling(ABM)approach which is a powerful tool for conducting community resilience analysis that simulates the behavior of different types of agents and their interactions to capture their interdependencies.The results are presented in the form of recovery time series as well as calculated resilience indices for various community systems(lifeline networks,schools,healthcare,businesses,and households).The results of this study can help deepen our understanding of how to efficiently expedite the recovery process of a community.
基金supported by the National Natural Science Foundation of China(52200228 and 72022004)the China Postdoctoral Science Foundation(2022M721817)the National Key Scientific Research Project(2021YFC3200200).
文摘Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises.This study developed a universal dynamic agent-based supply chain model to achieve tradeoffs between environmental risk reduction and economic sus-tainability.The model was used to conduct high-resolution daily simulations of the dynamic shifts in enterprise operations and their cascading effects on supply chain networks.It includes production,con-sumption,and transportation agents,attributing economic features to supply chain components and cap-turing their interactions.It also accounts for adaptive responses to daily external shocks and replicates realistic firm behaviors.By coupling high spatial-temporal resolution firm-level data from 18916 chemical enterprises,this study investigates the economic and environmental impacts of an environmen-tal policy resulting in the closure of 1800 chemical enterprises over three years.The results revealed a significant economic loss of 25.8 billion USD,ranging from 23.8 billion to 31.8 billion USD.Notably,over 80%of this loss was attributed to supply chain propagation.Counterfactual analyses indicated that imple-menting a staggered shutdown strategy prevented 18.8%of supply chain losses,highlighting the impor-tance of a gradual policy implementation to prevent abrupt supply chain disruptions.Furthermore,the study highlights the effectiveness of a multi-objective policy design in reducing economic losses(about 29%)and environmental risks(about 40%),substantially enhancing the efficiency of the environmental policy.The high-resolution simulations provide valuable insights for policy designers to formulate strategies with staggered implementation and multiple objectives to mitigate supply chain losses and environmental risks and ensure a sustainable future.
基金supported by the National Natural Science Foundation of China under Grant Nos.71771006 and 71771008。
文摘This paper proposes a novel agent-based model combining private information diffusion to explain time-series momentum and reversal.Private information transmission allows heterogeneous trading strategies coexist in the artificial market.The experiments reproduce momentum in short horizon and reversal in long horizon in the artificial financial market.Moreover,the authors also analyze how the private information contagion affects the momentum.Meanwhile,the authors find the significant price trend and excess volatility of volume when private information diffuses gradually.
文摘BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.
基金This work was supported in part by the National Natural Science Foundation of China[72101188]the Shanghai Municipal Science and Technology Major Project[2021SHZDZX0100]the Fundamental Research Funds for the Central Universities.
文摘The volume of instant delivery has witnessed a significant growth in recent years.Given the involvement of numerous heterogeneous stakeholders,instant delivery operations are inherently characterized by dynamics and uncertainties.This study introduces two order dispatching strategies,namely task buffering and dynamic batching,as potential solutions to address these challenges.The task buffering strategy aims to optimize the assignment timing of orders to couriers,thereby mitigating demand uncertainties.On the other hand,the dynamic batching strategy focuses on alleviating delivery pressure by assigning orders to couriers based on their residual capacity and extra delivery dis tances.To model the instant delivery problem and evaluate the performances of order dis patching strategies,Adaptive Agent-Based Order Dispatching(ABOD)approach is developed,which combines agent-based modelling,deep reinforcement learning,and the Kuhn-Munkres algorithm.The ABOD effectively captures the system’s uncertainties and heterogeneity,facilitating stakeholders learning in novel scenarios and enabling adap tive task buffering and dynamic batching decision-makings.The efficacy of the ABOD approach is verified through both synthetic and real-world case studies.Experimental results demonstrate that implementing the ABOD approach can lead to a significant increase in customer satisfaction,up to 275.42%,while simultaneously reducing the deliv ery distance by 11.38%compared to baseline policies.Additionally,the ABOD approach exhibits the ability to adaptively adjust buffering times to maintain high levels of customer satisfaction across various demand scenarios.As a result,this approach offers valuable sup port to logistics providers in making informed decisions regarding order dispatching in instant delivery operations.
文摘The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.
基金National Natural Science Foundation of China,No.41571098,No.41530749National Key R&D Program of China,No.2017YFC1502903,No.2018YFC1508805。
文摘Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems.As a process-oriented modelling approach,agent based model(ABM)plays an important role in revealing the driving forces of land change and understanding the process of land change.This paper starts from three aspects:The theory,application and modeling framework of ABM.First,we summarize the theoretical basis of ABM and introduce some related concepts.Then we expound the application and development of ABM in both urban land systems and agricultural land systems,and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region,China.On the basis of combing the ABM modeling protocol,we propose the land system ABM modeling framework and process from the perspective of agents.In terms of urban land use,ABM research initially focused on the study of urban expansion based on landscape,then expanded to issues like urban residential separation,planning and zoning,ecological functions,etc.In terms of agricultural land use,ABM application presents more diverse and individualized features.Research topics include farmers’behavior,farmers’decision-making,planting systems,agricultural policy,etc.Compared to traditional models,ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data.However,due to its unique bottom-up model structure,ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.
文摘Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant＇s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the ter- ritory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when： 1） there is a mismatch in nest- mate recognition cues and 2） each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin （5-HT） and octopamine （OA） modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and ag- gression. In this article, we develop and explore an agent-based model that conceptualizes how in- dividual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based de- cision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.
基金Project supported by the Talent Project Foundation of Zhejiang Province, China
文摘This work re-examined the simulation result of game analysis (Joshi et al., 2000) based on an agent-based model, Santa Fe Institute Artificial Stock Market. Allowing for recent research work on this artificial model, this paper’s modified game simulations found that the dividend amplitude parameter is a crucial factor and that the original conclusion still holds in a not long period, but only when the dividend amplitude is large enough. Our explanation of this result is that the dividend amplitude pa- rameter is a measurement of market uncertainty. The greater the uncertainty, the greater the price volatility, and so is the risk of investing in the stock market. The greater the risk, the greater the advantage of including technical rules.
基金provided by Marie Sklodowska-Curie ITN Horizon 2020-funded project INSIGHTS(call H2020-MSCA-ITN-2017,grant agreement n.765710)NWO—Nederlandse Organisatie voor Wetenschappelijk Onderzoek(Award Number:KIVI.2019.006 HUMAINER AI project)。
文摘Fraudulent actions of a trader or a group of traders can cause substantial disturbance to the market,both directly influencing the price of an asset or indirectly by misin-forming other market participants.Such behavior can be a source of systemic risk and increasing distrust for the market participants,consequences that call for viable countermeasures.Building on the foundations provided by the extant literature,this study aims to design an agent-based market model capable of reproducing the behavior of the Bitcoin market during the time of an alleged Bitcoin price manipulation that occurred between 2017 and early 2018.The model includes the mechanisms of a limit order book market and several agents associated with different trading strategies,including a fraudulent agent,initialized from empirical data and who performs market manipulation.The model is validated with respect to the Bitcoin price as well as the amount of Bitcoins obtained by the fraudulent agent and the traded volume.Simulation results provide a satisfactory fit to historical data.Several price dips and volume anomalies are explained by the actions of the fraudulent trader,completing the known body of evidence extracted from blockchain activity.The model suggests that the presence of the fraudulent agent was essential to obtain Bitcoin price development in the given time period;without this agent,it would have been very unlikely that the price had reached the heights as it did in late 2017.The insights gained from the model,especially the connection between liquidity and manipulation efficiency,unfold a discussion on how to prevent illicit behavior.
基金supported by the National Natural Science Foundation of China (No.21273209)
文摘Ulcerative colitis, an inflammatory bowel disease, is a chronic inflammatory disorder that results in ulcers of the colon and rectum without known etiology. Ulcerative colitis causes a huge public health care burden particularly in developed countries. Many studies suggest that ulcerative colitis results from an abnormal immune response against components of cornrnensal rnicrobiota in genetically susceptible individuals. However, understanding of the disease mechanisms at cellular and molecular levels remains largely elusive. In this paper, a network model is developed based on our previous study and computer simulations are perforrned using an agent-based network modeling to elucidate the dynamics of immune response in ulcerative colitis progression. Our modeling study identifies several important positive feedback loops as a driving force for ulcerative colitis initiation and progression. The results demonstrate that although immune response in ulcerative colitis patients is dominated by anti-inflarnrnatory/regulatory cells such as alternatively activated rnacrophages and type II natural killer T cells, proinflarnrnatory cells including classically activated rnacrophages, T helper 1 and T helper 17 cells, and their secreted cytokines tumor necrosis factor-α, interleukin-12, interleukin-23, interleukin-17 and interferon-γ remain at certain levels （lower than those in Crohn＇s disease, another inflammatory bowel disease）. Long-terrn exposure to these proinflarnrnatory components, causes rnucosal tissue damage persistently, leading to ulcerative colitis. Our simulation results are qualitatively in agreement with clinical and laboratory measurements, offering novel insight into the disease mechanisms.
文摘Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.
文摘Agent-based models (ABMs) are capable of constructing individual system components at different levels of representation to describe non-linear relationships between those components. Compared to a traditional mathematical modeling approach, agent-based models have an inherent spatial component with which they can easily describe local interactions and environmental heterogeneity. Furthermore, agent-based model maps interactions among agents inherently to the biological phenomenon by embedding the stochastic nature and dynamics transitions, thereby demonstrating suitability for the development of complex biological processes. Recently, an abundance of literature has presented application of agent-based modeling in the biological system. This review focuses on application of agent-based modeling to progression in simulation of infectious disease in the human immune system and discusses advantages and disadvantages of agent-based modeling application. Finally, potential implementation of agent-based modeling in relation to infectious disease modeling in future research is explored.
