Understanding migratory waterfowl spatiotemporal distributions is important because,in addition to their economic and cultural value,wild waterfowl can be infectious reservoirs of highly pathogenic avian influenza vir...Understanding migratory waterfowl spatiotemporal distributions is important because,in addition to their economic and cultural value,wild waterfowl can be infectious reservoirs of highly pathogenic avian influenza virus(HPAIV).Waterfowl migration has been implicated in regional and intercontinental HPAIV dispersal,and predictive capabilities of where and when HPAIV may be introduced to susceptible spillover hosts would facilitate biosecurity and mitigation efforts.To develop forecasts for HPAIV dispersal,an improved understanding of how individual birds interact with their environment and move on a landscape scale is required.Using an agent-based modeling approach,we integrated individual-scale energetics,species-specific morphology and behavior,and landscape-scale weather and habitat data in a mechanistic stochastic framework to simulate Mallard(Anas platyrhynchos)and Northern Pintail(Anas acuta)annual migration across the Northern Hemisphere.Our model recreated biologically realistic migratory patterns using a first principles approach to waterfowl ecology,behavior,and physiology.Conducting a limited structural sensitivity analysis comparing reduced models to eBird Status and Trends in reference to the full model,we identified density dependence as the main factor influencing spring migration and breeding distributions,and wind as the main factor influencing fall migration and overwintering distributions.We show evidence of weather patterns in Northeast Asia causing significant intercontinental pintail migration to North America.By linking individual energetics to landscapescale processes,we identify key drivers of waterfowl migration while developing a predictive model responsive to daily weather patterns.This model paves the way for future waterfowl migration research predicting HPAIV transmission,climate change impacts,and oil spill effects.展开更多
The laser weapons will play a special role in the future high-tech war.To study the impact of airborne laser weapon on the System-of-System(SoS)effectiveness in cooperative com-bat,this paper proposes an indicator con...The laser weapons will play a special role in the future high-tech war.To study the impact of airborne laser weapon on the System-of-System(SoS)effectiveness in cooperative com-bat,this paper proposes an indicator construction method based on the combination of the weapon capability indicator system and the combat simulation.The indicator system of capability is divided into 4 layers by the bottom-to-up generation mechanism of indicators.It can describe the logical relationship between the indicator layers from a qualitative perspective.Together with the 4 layers capability indicator system,a hierarchical framework of airborne laser weapon is established by the agent-based modeling and simulation.Impact analyses show that the SoS effectiveness improves with the increase of the laser weapon output power,the laser launcher diameter,and the photoelectric sensor pixel.But the SoS effectiveness promotion brought by the photoelectric sensor pixel is limited.The results can be used for the development of tactical airborne laser weapon.展开更多
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...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。展开更多
At present, how to enable Search Engine to construct user personal interest model initially, master user＇s personalized information timely and provide personalized services accurately have become the hotspot in the r...At present, how to enable Search Engine to construct user personal interest model initially, master user＇s personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model＇s construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model （UIM） is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile （UIP） are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.展开更多
This paper proposes an original behavioural finance representative agent model,to explain how fake news’empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis.The model r...This paper proposes an original behavioural finance representative agent model,to explain how fake news’empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis.The model reconciles empirically-observed price overreactions to fake news with empirically-observed price underreactions to real news,and predicts a novel secondary impact of fake news:that fake news in a security amplifies underreactions to subsequent real news for the security.Evaluating the model against a large-sample event study of the 2019 Chinese ADR Delisting Threat fake news and debunking event,this paper finds strong qualitative validation for its model’s dynamics and predictions.展开更多
This paper is devoted to analyze and model user reading and replying activities in a bulletin board system （BBS） social network. By analyzing the data set from a famous Chinese BBS social network, we show how some u...This paper is devoted to analyze and model user reading and replying activities in a bulletin board system （BBS） social network. By analyzing the data set from a famous Chinese BBS social network, we show how some user activities distribute, and reveal several important features that might characterize user dynamics. We propose a method to model user activities in the BBS social network. The model could reproduce power-law and non-power-law distributions of user activities at the same time. Our results show that user reading and replying activities could be simulated through simple agent-based models. Specifically, manners of how the BBS server interacts with Internet users in the Web 2.0 application, how users organize their reading lists, and how user behavioral trait distributes are the important factors in the formation of activity patterns.展开更多
Agents response equilibrium (ARE) model has been taken advantage of to build a multi-agent system for analyzing fiscal policy effect. Through establishing various types of economic entities and endowing them with abil...Agents response equilibrium (ARE) model has been taken advantage of to build a multi-agent system for analyzing fiscal policy effect. Through establishing various types of economic entities and endowing them with abilities to react and make decision, the whole system will evolve to new conditions in response to policy change. Compared with different scenarios, it can be concluded that when raising taxation ratio, sectoral scale will shrink to some extent. But supported by government expenditure, certain sectors could be kept in comparatively larger production scale.展开更多
This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system...This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system is built,where each agent stands for a vehicle,and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent-based model captures the nonlinear feedback between vehicle routing behaviors and road-network congestion status.Secondly,a hybrid routing selection strategy is provided,which guides the vehicle routes adapting to the realtime road-network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution,by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road-network. Finally,we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And,the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom-up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.展开更多
Occupant behaviour has significant impacts on the performance of machine learning algorithms when predicting building energy consumption.Due to a variety of reasons(e.g.,underperforming building energy management syst...Occupant behaviour has significant impacts on the performance of machine learning algorithms when predicting building energy consumption.Due to a variety of reasons(e.g.,underperforming building energy management systems or restrictions due to privacy policies),the availability of occupational data has long been an obstacle that hinders the performance of machine learning algorithms in predicting building energy consumption.Therefore,this study proposed an agent⁃based machine learning model whereby agent⁃based modelling was employed to generate simulated occupational data as input features for machine learning algorithms for building energy consumption prediction.Boruta feature selection was also introduced in this study to select all relevant features.The results indicated that the performances of machine learning algorithms in predicting building energy consumption were significantly improved when using simulated occupational data,with even greater improvements after conducting Boruta feature selection.展开更多
The main purpose of establishing a complex agent network （CAN） search model is to specifically model each type of the relationships between different types of Agent structure domain and make it easier to be implemen...The main purpose of establishing a complex agent network （CAN） search model is to specifically model each type of the relationships between different types of Agent structure domain and make it easier to be implemented in the existing programming language environment. Under the guidance of complex Agent network method, CAN search process was analyzed, a dynamic search model description was established based on CAN search process, and then individual Agent modelling and the memory and processing of the thinking attributes such as beliefs, desires and intentions in CAN search process were mainly introduced from the individual level; all sorts of Agent conceptual models and Agent type descriptions for CAN search model were designed by introducing BDI Agent; the states and behaviors of the Agent involving in CAN search process were clearly defined.展开更多
Heterogeneous platforms collaborate to execute tasks through different operational models,resulting in the task allocation problem that incorporates different agent models.In this paper,we address the problem of coope...Heterogeneous platforms collaborate to execute tasks through different operational models,resulting in the task allocation problem that incorporates different agent models.In this paper,we address the problem of cooperative target allocation for heterogeneous agent models,where we design the task-agent mathing model and the multi-agent routing model.Since the heterogeneity and cooperativity of agent models lead to a coupled allocation problem,we propose a matrix-encoding genetic algorithm(MEGA)to plan reliable allocation schemes.Specifically,an integer matrix encoding is resorted to represent the priority between targets and agents in MEGA and a ranking rule is designed to decode the priority matrix.Based on the proposed encoding-decoding framework,we use the discrete and continuous optimization operators to update the target-agent match pairs and task execution orders.In addition,to adaptively balance the diversity and intensification of the population,a dynamical supplement strategy based on Hamming dis-tance is proposed.This strategy adds individuals with different diversity and fitness at different stages of the optimization process.Finally,simulation experiments show that MEGA algorithm outperforms the conventional target allocation algorithms in the heterogeneous agent scenario.展开更多
Next-generation nuclear reactor technologies,such as molten salt and fast reactors present complex analytical challenges that require advanced modeling and simulation tools.Yet,traditional workflows for Monte Carlo si...Next-generation nuclear reactor technologies,such as molten salt and fast reactors present complex analytical challenges that require advanced modeling and simulation tools.Yet,traditional workflows for Monte Carlo simulations like FLUKA are labor-intensive and error-prone,relying on manual input file generation and postprocessing.This limits scalability and efficiency.In this work,we present AutoFLUKA,a novel framework that leverages domain knowledge-embedded large language models(LLMs)and AI agents to automate the entire FLUKA simulation workflow from input file creation to execution management,and data analysis.AutoFLUKA also integrates Retrieval-Augmented Generation(RAG)and a web-based user-friendly graphical interface,enabling users to interact with the system in real time.Benchmarking against manual FLUKA simulations,AutoFLUKA demonstrated substantial improvements in resolving FLUKA error-related queries,particularly those arising from input file creation and execution.Traditionally,such issues are addressed through expert support on the FLUKA user forum,often resulting in significant delays.The resolution time for these queries was also reduced from several days to under one minute.Additionally,human-induced simulation errors were mitigated,and a high accuracy in key simulation metrics,such as neutron fluence and microdosimetric quantities,was achieved,with uncertainties below 0.001%for large sample sizes.The flexibility of AutoFLUKA was demonstrated through successful application to both general and specialized nuclear scenarios,and its design allows for straightforward extension to other simulation platforms.These results highlight AutoFLUKA’s potential to transform nuclear engineering analysis by enhancing productivity,reliability,and accessibility through AI-driven automation.展开更多
Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experimen...Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.展开更多
The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of inte...The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of interactions, the duration over which individual variation in interactions persists may affect how the network operates. Individuals may persist in their behavior over time and across situations, often referred to as personality. Colonies of social insects are an example of a biological system in which the structure of the coordinated networks of interacting workers may greatly influence information flow within the colony, and therefore its collective behavior. Here I investigate the effects of persistence in walking patterns on interaction networks us- ing computer simulations that are parameterized using observed behavior of harvester ants. I examine how the duration of persis- tence in spatial behavior influences network structure. Furthermore, I explore how spatial features of the environment affect the relationship between persistent behavior and network structure. I show that as persistence increases, the skewness of the weighted degree distribution of the interaction network increases. However, this relationship holds only when ants are confined in a space with boundaries, but not when physical barriers are absent. These findings suggest that the influence of animal personalities on network structure and function depends on the environment in which the animals reside [Current Zoology 61 （1）： 98-106, 2015].展开更多
An agent in the decision support system (DSS) has to cope with quantitative analysis processing normally. However, from the view of agent working style, the agent oriented aid modeling operations need new procedure ...An agent in the decision support system (DSS) has to cope with quantitative analysis processing normally. However, from the view of agent working style, the agent oriented aid modeling operations need new procedure accepted by the agent. For example, in the distributed activity planning processes, the transforming problem description has to use a unified pattern first, then to compute the activity′s 6 time parameters, activity′s duration, entity plan scheme, optimal calculation and so on. In this paper, we propose a process manner of agent oriented modeling for the distributed activity network. The goal is to introduce an agent working procedure included model usage, multi agent cooperating, communicating among agents and interaction between system and human. Also, it included the problem representation, the initial process, agent design, transform and the computing with interaction in detail.展开更多
Active government intervention is a striking characteristic of the Chinese stock market.This study develops a behavioral heterogeneous agent model(HAM)comprising fundamentalists,chartists,and stabilizers to investigat...Active government intervention is a striking characteristic of the Chinese stock market.This study develops a behavioral heterogeneous agent model(HAM)comprising fundamentalists,chartists,and stabilizers to investigate investors’dynamic switching mechanisms under government intervention.The model introduces a new player,the stabilizer,into the HAM as a proxy for the government.We use the model to examine government programs during the 2015 China stock market crash and find that it can replicate the dynamics of investor sentiment and asset prices.In addition,our analysis of two simulations,specifically the data-generating processes and shock response analysis,further corroborates the key conclusion that our intervention model not only maintains market stability but also promotes the return of risk asset prices to their fun-damental values.The study concludes that government interventions guided by the new HAM can alleviate the dilemma between reducing price volatility and improving price efficiency in future intervention programs.展开更多
We present a mathematical model of a day care center in a developed country (such as Canada), in order to use it for the estimation of individual-to-individual contact rates in young age groups and in an educational g...We present a mathematical model of a day care center in a developed country (such as Canada), in order to use it for the estimation of individual-to-individual contact rates in young age groups and in an educational group setting. In our model, individuals in the population are children (ages 1.5 to 4 years) and staff, and their interactions are modelled explicitly: person-to-person and person-to-environment, with a very high time resolution. Their movement and meaningful contact patterns are simulated and then calibrated with collected data from a child care facility as a case study. We present these calibration results as a first part in the further development of our model for testing and estimating the spread of infectious diseases within child care centers.展开更多
文摘Understanding migratory waterfowl spatiotemporal distributions is important because,in addition to their economic and cultural value,wild waterfowl can be infectious reservoirs of highly pathogenic avian influenza virus(HPAIV).Waterfowl migration has been implicated in regional and intercontinental HPAIV dispersal,and predictive capabilities of where and when HPAIV may be introduced to susceptible spillover hosts would facilitate biosecurity and mitigation efforts.To develop forecasts for HPAIV dispersal,an improved understanding of how individual birds interact with their environment and move on a landscape scale is required.Using an agent-based modeling approach,we integrated individual-scale energetics,species-specific morphology and behavior,and landscape-scale weather and habitat data in a mechanistic stochastic framework to simulate Mallard(Anas platyrhynchos)and Northern Pintail(Anas acuta)annual migration across the Northern Hemisphere.Our model recreated biologically realistic migratory patterns using a first principles approach to waterfowl ecology,behavior,and physiology.Conducting a limited structural sensitivity analysis comparing reduced models to eBird Status and Trends in reference to the full model,we identified density dependence as the main factor influencing spring migration and breeding distributions,and wind as the main factor influencing fall migration and overwintering distributions.We show evidence of weather patterns in Northeast Asia causing significant intercontinental pintail migration to North America.By linking individual energetics to landscapescale processes,we identify key drivers of waterfowl migration while developing a predictive model responsive to daily weather patterns.This model paves the way for future waterfowl migration research predicting HPAIV transmission,climate change impacts,and oil spill effects.
文摘The laser weapons will play a special role in the future high-tech war.To study the impact of airborne laser weapon on the System-of-System(SoS)effectiveness in cooperative com-bat,this paper proposes an indicator construction method based on the combination of the weapon capability indicator system and the combat simulation.The indicator system of capability is divided into 4 layers by the bottom-to-up generation mechanism of indicators.It can describe the logical relationship between the indicator layers from a qualitative perspective.Together with the 4 layers capability indicator system,a hierarchical framework of airborne laser weapon is established by the agent-based modeling and simulation.Impact analyses show that the SoS effectiveness improves with the increase of the laser weapon output power,the laser launcher diameter,and the photoelectric sensor pixel.But the SoS effectiveness promotion brought by the photoelectric sensor pixel is limited.The results can be used for the development of tactical airborne laser weapon.
文摘目的: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。
基金Supported by the National Natural Science Foundation of China (50674086)the Doctoral Foundation of Ministry of Education of China (20060290508)the Youth Scientific Research Foundation of CUMT (0D060125)
文摘At present, how to enable Search Engine to construct user personal interest model initially, master user＇s personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model＇s construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model （UIM） is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile （UIP） are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.
文摘This paper proposes an original behavioural finance representative agent model,to explain how fake news’empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis.The model reconciles empirically-observed price overreactions to fake news with empirically-observed price underreactions to real news,and predicts a novel secondary impact of fake news:that fake news in a security amplifies underreactions to subsequent real news for the security.Evaluating the model against a large-sample event study of the 2019 Chinese ADR Delisting Threat fake news and debunking event,this paper finds strong qualitative validation for its model’s dynamics and predictions.
基金supported in part by the National Natural Science Foundation of China under Grant No. 60972010the Beijing Natural Science Foundation under Grant No. 4102047+1 种基金the Major Program for Research on Philosophy & Humanity Social Sciences of the Ministry of Education of China under Grant No. 08WL1101the Service Business of Scientists and Engineers Project under Grant No. 2009GJA00048
文摘This paper is devoted to analyze and model user reading and replying activities in a bulletin board system （BBS） social network. By analyzing the data set from a famous Chinese BBS social network, we show how some user activities distribute, and reveal several important features that might characterize user dynamics. We propose a method to model user activities in the BBS social network. The model could reproduce power-law and non-power-law distributions of user activities at the same time. Our results show that user reading and replying activities could be simulated through simple agent-based models. Specifically, manners of how the BBS server interacts with Internet users in the Web 2.0 application, how users organize their reading lists, and how user behavioral trait distributes are the important factors in the formation of activity patterns.
文摘Agents response equilibrium (ARE) model has been taken advantage of to build a multi-agent system for analyzing fiscal policy effect. Through establishing various types of economic entities and endowing them with abilities to react and make decision, the whole system will evolve to new conditions in response to policy change. Compared with different scenarios, it can be concluded that when raising taxation ratio, sectoral scale will shrink to some extent. But supported by government expenditure, certain sectors could be kept in comparatively larger production scale.
基金Sponsored by the Natural Science Foundation of Hunan ProvinceChina(Grant No.13JJ3049)the Fundamental Research Funds for the Central Universities(Grant No.2012AA01A301-1)
文摘This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system is built,where each agent stands for a vehicle,and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent-based model captures the nonlinear feedback between vehicle routing behaviors and road-network congestion status.Secondly,a hybrid routing selection strategy is provided,which guides the vehicle routes adapting to the realtime road-network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution,by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road-network. Finally,we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And,the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom-up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.
文摘Occupant behaviour has significant impacts on the performance of machine learning algorithms when predicting building energy consumption.Due to a variety of reasons(e.g.,underperforming building energy management systems or restrictions due to privacy policies),the availability of occupational data has long been an obstacle that hinders the performance of machine learning algorithms in predicting building energy consumption.Therefore,this study proposed an agent⁃based machine learning model whereby agent⁃based modelling was employed to generate simulated occupational data as input features for machine learning algorithms for building energy consumption prediction.Boruta feature selection was also introduced in this study to select all relevant features.The results indicated that the performances of machine learning algorithms in predicting building energy consumption were significantly improved when using simulated occupational data,with even greater improvements after conducting Boruta feature selection.
文摘The main purpose of establishing a complex agent network （CAN） search model is to specifically model each type of the relationships between different types of Agent structure domain and make it easier to be implemented in the existing programming language environment. Under the guidance of complex Agent network method, CAN search process was analyzed, a dynamic search model description was established based on CAN search process, and then individual Agent modelling and the memory and processing of the thinking attributes such as beliefs, desires and intentions in CAN search process were mainly introduced from the individual level; all sorts of Agent conceptual models and Agent type descriptions for CAN search model were designed by introducing BDI Agent; the states and behaviors of the Agent involving in CAN search process were clearly defined.
基金supportedinpart by the National Natural Science Foundation of China(62371379 and 62371447).
文摘Heterogeneous platforms collaborate to execute tasks through different operational models,resulting in the task allocation problem that incorporates different agent models.In this paper,we address the problem of cooperative target allocation for heterogeneous agent models,where we design the task-agent mathing model and the multi-agent routing model.Since the heterogeneity and cooperativity of agent models lead to a coupled allocation problem,we propose a matrix-encoding genetic algorithm(MEGA)to plan reliable allocation schemes.Specifically,an integer matrix encoding is resorted to represent the priority between targets and agents in MEGA and a ranking rule is designed to decode the priority matrix.Based on the proposed encoding-decoding framework,we use the discrete and continuous optimization operators to update the target-agent match pairs and task execution orders.In addition,to adaptively balance the diversity and intensification of the population,a dynamical supplement strategy based on Hamming dis-tance is proposed.This strategy adds individuals with different diversity and fitness at different stages of the optimization process.Finally,simulation experiments show that MEGA algorithm outperforms the conventional target allocation algorithms in the heterogeneous agent scenario.
基金supported by the US Department of Energy Office of Nuclear Energy Distinguished Early Career Program under contract number DE-NE0009468support is provided by the Texas A&M Institute of Data Science(TAMIDS)Seed Program for AI,Computing,and Data Science。
文摘Next-generation nuclear reactor technologies,such as molten salt and fast reactors present complex analytical challenges that require advanced modeling and simulation tools.Yet,traditional workflows for Monte Carlo simulations like FLUKA are labor-intensive and error-prone,relying on manual input file generation and postprocessing.This limits scalability and efficiency.In this work,we present AutoFLUKA,a novel framework that leverages domain knowledge-embedded large language models(LLMs)and AI agents to automate the entire FLUKA simulation workflow from input file creation to execution management,and data analysis.AutoFLUKA also integrates Retrieval-Augmented Generation(RAG)and a web-based user-friendly graphical interface,enabling users to interact with the system in real time.Benchmarking against manual FLUKA simulations,AutoFLUKA demonstrated substantial improvements in resolving FLUKA error-related queries,particularly those arising from input file creation and execution.Traditionally,such issues are addressed through expert support on the FLUKA user forum,often resulting in significant delays.The resolution time for these queries was also reduced from several days to under one minute.Additionally,human-induced simulation errors were mitigated,and a high accuracy in key simulation metrics,such as neutron fluence and microdosimetric quantities,was achieved,with uncertainties below 0.001%for large sample sizes.The flexibility of AutoFLUKA was demonstrated through successful application to both general and specialized nuclear scenarios,and its design allows for straightforward extension to other simulation platforms.These results highlight AutoFLUKA’s potential to transform nuclear engineering analysis by enhancing productivity,reliability,and accessibility through AI-driven automation.
文摘Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.
文摘The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of interactions, the duration over which individual variation in interactions persists may affect how the network operates. Individuals may persist in their behavior over time and across situations, often referred to as personality. Colonies of social insects are an example of a biological system in which the structure of the coordinated networks of interacting workers may greatly influence information flow within the colony, and therefore its collective behavior. Here I investigate the effects of persistence in walking patterns on interaction networks us- ing computer simulations that are parameterized using observed behavior of harvester ants. I examine how the duration of persis- tence in spatial behavior influences network structure. Furthermore, I explore how spatial features of the environment affect the relationship between persistent behavior and network structure. I show that as persistence increases, the skewness of the weighted degree distribution of the interaction network increases. However, this relationship holds only when ants are confined in a space with boundaries, but not when physical barriers are absent. These findings suggest that the influence of animal personalities on network structure and function depends on the environment in which the animals reside [Current Zoology 61 （1）： 98-106, 2015].
文摘An agent in the decision support system (DSS) has to cope with quantitative analysis processing normally. However, from the view of agent working style, the agent oriented aid modeling operations need new procedure accepted by the agent. For example, in the distributed activity planning processes, the transforming problem description has to use a unified pattern first, then to compute the activity′s 6 time parameters, activity′s duration, entity plan scheme, optimal calculation and so on. In this paper, we propose a process manner of agent oriented modeling for the distributed activity network. The goal is to introduce an agent working procedure included model usage, multi agent cooperating, communicating among agents and interaction between system and human. Also, it included the problem representation, the initial process, agent design, transform and the computing with interaction in detail.
基金the National Natural Science Foundation of China(Grant Nos.72261002,72201132,71790594)the Youth Foundation for Humanities and Social Sciences Research of the Ministry of Education(No.22YJC790190)+2 种基金the Guizhou Provincial Science and Technology Projects(No.[2019]5103)the Guizhou Key Laboratory of Big Data Statistical Analysis(No.BDSA20200105)the Open Project of Jiangsu Key Laboratory of Financial Engineering(NSK2021-18)。
文摘Active government intervention is a striking characteristic of the Chinese stock market.This study develops a behavioral heterogeneous agent model(HAM)comprising fundamentalists,chartists,and stabilizers to investigate investors’dynamic switching mechanisms under government intervention.The model introduces a new player,the stabilizer,into the HAM as a proxy for the government.We use the model to examine government programs during the 2015 China stock market crash and find that it can replicate the dynamics of investor sentiment and asset prices.In addition,our analysis of two simulations,specifically the data-generating processes and shock response analysis,further corroborates the key conclusion that our intervention model not only maintains market stability but also promotes the return of risk asset prices to their fun-damental values.The study concludes that government interventions guided by the new HAM can alleviate the dilemma between reducing price volatility and improving price efficiency in future intervention programs.
文摘We present a mathematical model of a day care center in a developed country (such as Canada), in order to use it for the estimation of individual-to-individual contact rates in young age groups and in an educational group setting. In our model, individuals in the population are children (ages 1.5 to 4 years) and staff, and their interactions are modelled explicitly: person-to-person and person-to-environment, with a very high time resolution. Their movement and meaningful contact patterns are simulated and then calibrated with collected data from a child care facility as a case study. We present these calibration results as a first part in the further development of our model for testing and estimating the spread of infectious diseases within child care centers.
