Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain an...Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain and the general-director chain,to handle the trade-off between technical and management decisions. However, previous works on organization search have mainly focused on the single-chain hierarchical organization in which all decisions are regarded as homogeneous. The heterogeneity and the interdependency between technical decisions and management decisions have been neglected. A two-chain hierarchical organization structure mapped from a real complex project is constructed. Then, a discrete decision model for a Liang Zong two-chain hierarchical organization in an NK model framework is proposed. This model proves that this kind of organization structure can reduce the search space by a large amount and that the search process should reach a final stable state more quickly. For a more complicated decision mechanism, a multi-agent simulation based on the above NK model is used to explore the effect of the two-chain organization structure on the speed, stability, and performance of the search process. The results provide three insights into how, compared with the single-chain hierarchical organization, the two-chain organization can improve the search process: it can reduce the number of iterations efficiently; the search is more stable because the search space is a smoother hill-like fitness landscape; in general, the search performance can be improved.However, when the organization structure is very complicated, the performance of a two-chain organization is inferior to that of a single-chain organization. These findings about the efficiency of the unique Chinese-style organization structure can be used to guide organization design for complex projects.展开更多
In this paper,a theoretical framework of Multiagent Simulation(MAS)is proposed for strategic bidding in electricity markets using reinforcement learning,which consists of two parts:one is a MAS system used to simulate...In this paper,a theoretical framework of Multiagent Simulation(MAS)is proposed for strategic bidding in electricity markets using reinforcement learning,which consists of two parts:one is a MAS system used to simulate the competitive bidding of the actual electricity market;the other is an adaptive learning strategy bidding system used to provide agents with more intelligent bidding strategies.An ExperienceWeighted Attraction(EWA)reinforcement learning algorithm(RLA)is applied to the MAS model and a new MAS method is presented for strategic bidding in electricity markets using a new Improved EWA(IEWA).From both qualitative and quantitative perspectives,it is compared with three other MAS methods using the Roth-Erev(RE),Q-learning and EWA.The results show that the performance of the MAS method using IEWA is proved to be better than the others.The four MAS models using four RLAs are built for strategic bidding in electricity markets.Through running the four MAS models,the rationality and correctness of the four MAS methods are verified for strategic bidding in electricity markets using reinforcement learning.展开更多
Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metavers...Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach outperforms the MAPPO approach by around 2% and effectively reduces approximately 20% of the latency of avatar task execution in UAV-assisted vehicular Metaverses.展开更多
The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameteri...The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.展开更多
Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas,and it is also the boundary of the solar wind energy transport to the magnetosphere.Soft X-ray imaging ...Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas,and it is also the boundary of the solar wind energy transport to the magnetosphere.Soft X-ray imaging allows investigation of the large-scale magnetopause by providing a two-dimensional(2-D)global view from a satellite.By performing 3-D global hybrid-particle-in-cell(hybrid-PIC)simulations,we obtain soft X-ray images of Earth’s magnetopause under different solar wind conditions,such as different plasma densities and directions of the southward interplanetary magnetic field.In all cases,magnetic reconnection occurs at low latitude magnetopause.The soft X-ray images observed by a hypothetical satellite are shown,with all of the following identified:the boundary of the magnetopause,the cusps,and the magnetosheath.Local X-ray emissivity in the magnetosheath is characterized by large amplitude fluctuations(up to 160%);however,the maximum line-of-sight-integrated X-ray intensity matches the tangent directions of the magnetopause well,indicating that these fluctuations have limited impact on identifying the magnetopause boundary in the X-ray images.Moreover,the magnetopause boundary can be identified using multiple viewing geometries.We also find that solar wind conditions have little effect on the magnetopause identification.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will provide X-ray images of the magnetopause for the first time,and our global hybrid-PIC simulation results can help better understand the 2-D X-ray images of the magnetopause from a 3-D perspective,with particle kinetic effects considered.展开更多
We derived the properties of the terrestrial magnetopause(MP)from two modeling approaches,one global–fluid,the other local–kinetic,and compared the results with data collected in situ by the Magnetospheric Multiscal...We derived the properties of the terrestrial magnetopause(MP)from two modeling approaches,one global–fluid,the other local–kinetic,and compared the results with data collected in situ by the Magnetospheric Multiscale 2(MMS2)spacecraft.We used global magnetohydrodynamic(MHD)simulations of the Earth’s magnetosphere(publicly available from the NASA-CCMC[National Aeronautics and Space Administration–Community Coordinated Modeling Center])and local Vlasov equilibrium models(based on kinetic models for tangential discontinuities)to extract spatial profiles of the plasma and field variables at the Earth’s MP.The global MHD simulations used initial solar wind conditions extracted from the OMNI database at the time epoch when the MMS2 observes the MP.The kinetic Vlasov model used asymptotic boundary conditions derived from the same in situ MMS measurements upstream or downstream of the MP.The global MHD simulations provide a three-dimensional image of the magnetosphere at the time when the MMS2 crosses the MP.The Vlasov model provides a one-dimensional local view of the MP derived from first principles of kinetic theory.The MMS2 experimental data also serve as a reference for comparing and validating the numerical simulations and modeling.We found that the MP transition layer formed in global MHD simulations was generally localized closer to the Earth(roughly by one Earth radius)from the position of the real MP observed by the MMS.We also found that the global MHD simulations overestimated the thickness of the MP transition by one order of magnitude for three analyzed variables:magnetic field,density,and tangential speed.The MP thickness derived from the local Vlasov equilibrium was consistent with observations for all three of these variables.The overestimation of density in the Vlasov equilibrium was reduced compared with the global MHD solutions.We discuss our results in the context of future SMILE(Solar wind Magnetosphere Ionosphere Link Explorer)campaigns for observing the Earth’s MP.展开更多
Solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing tech...Solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing techniques.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)and Lunar Environment heliospheric X-ray Imager(LEXI)missions aim to obtain soft Xray images of near-Earth space thanks to their Soft X-ray Imager(SXI)instruments.While earlier modeling works have already simulated soft X-ray images as might be obtained by SMILE SXI during its mission,the numerical models used so far are all based on the magnetohydrodynamics description of the space plasma.To investigate the possible signatures of ion-kinetic-scale processes in soft Xray images,we use for the first time a global hybrid-Vlasov simulation of the geospace from the Vlasiator model.The simulation is driven by fast and tenuous solar wind conditions and purely southward interplanetary magnetic field.We first produce global X-ray images of the dayside near-Earth space by placing a virtual imaging satellite at two different locations,providing meridional and equatorial views.We then analyze regional features present in the images and show that they correspond to signatures in soft X-ray emissions of mirrormode wave structures in the magnetosheath and flux transfer events(FTEs)at the magnetopause.Our results suggest that,although the time scales associated with the motion of those transient phenomena will likely be significantly smaller than the integration time of the SMILE and LEXI imagers,mirror-mode structures and FTEs can cumulatively produce detectable signatures in the soft X-ray images.For instance,a local increase by 30%in the proton density at the dayside magnetopause resulting from the transit of multiple FTEs leads to a 12%enhancement in the line-of-sight-and time-integrated soft X-ray emissivity originating from this region.Likewise,a proton density increase by 14%in the magnetosheath associated with mirror-mode structures can result in an enhancement in the soft X-ray signal by 4%.These are likely conservative estimates,given that the solar wind conditions used in the Vlasiator run can be expected to generate weaker soft X-ray emissions than the more common denser solar wind.These results will contribute to the preparatory work for the SMILE and LEXI missions by providing the community with quantitative estimates of the effects of small-scale,transient phenomena occurring on the dayside.展开更多
Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that ...Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline experience.Besides, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.展开更多
Multi-agent reinforcement learning(MARL)has been a rapidly evolving field.This paper presents a comprehensive survey of MARL and its applications.We trace the historical evolution of MARL,highlight its progress,and di...Multi-agent reinforcement learning(MARL)has been a rapidly evolving field.This paper presents a comprehensive survey of MARL and its applications.We trace the historical evolution of MARL,highlight its progress,and discuss related survey works.Then,we review the existing works addressing inherent challenges and those focusing on diverse applications.Some representative stochastic games,MARL means,spatial forms of MARL,and task classification are revisited.We then conduct an in-depth exploration of a variety of challenges encountered in MARL applications.We also address critical operational aspects,such as hyperparameter tuning and computational complexity,which are pivotal in practical implementations of MARL.Afterward,we make a thorough overview of the applications of MARL to intelligent machines and devices,chemical engineering,biotechnology,healthcare,and societal issues,which highlights the extensive potential and relevance of MARL within both current and future technological contexts.Our survey also encompasses a detailed examination of benchmark environments used in MARL research,which are instrumental in evaluating MARL algorithms and demonstrate the adaptability of MARL to diverse application scenarios.In the end,we give our prospect for MARL and discuss their related techniques and potential future applications.展开更多
This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theor...This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.展开更多
The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology...The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in MS-Excel.Focused on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning requirements.The chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an escalation.The SS approach showed exceptional efficacy in calculating odds of failure that are notably low.Within computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO models.The ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most promising.This study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation infrastructure.These findings contribute to the enhancement of safety and reliability in real-world situations.展开更多
This paper investigates the problem of global/semi-global finite-time consensus for integrator-type multi-agent sys-tems.New hyperbolic tangent function-based protocols are pro-posed to achieve global and semi-global ...This paper investigates the problem of global/semi-global finite-time consensus for integrator-type multi-agent sys-tems.New hyperbolic tangent function-based protocols are pro-posed to achieve global and semi-global finite-time consensus for both single-integrator and double-integrator multi-agent systems with leaderless undirected and leader-following directed commu-nication topologies.These new protocols not only provide an explicit upper-bound estimate for the settling time,but also have a user-prescribed bounded control level.In addition,compared to some existing results based on the saturation function,the pro-posed approach considerably simplifies the protocol design and the stability analysis.Illustrative examples and an application demonstrate the effectiveness of the proposed protocols.展开更多
基金supported by the National Natural Science Foundation of China(7157105771390522)the Key Lab for Public Engineering Audit of Jiangsu Province,Nanjing Audit University(GGSS2016-08)
文摘Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain and the general-director chain,to handle the trade-off between technical and management decisions. However, previous works on organization search have mainly focused on the single-chain hierarchical organization in which all decisions are regarded as homogeneous. The heterogeneity and the interdependency between technical decisions and management decisions have been neglected. A two-chain hierarchical organization structure mapped from a real complex project is constructed. Then, a discrete decision model for a Liang Zong two-chain hierarchical organization in an NK model framework is proposed. This model proves that this kind of organization structure can reduce the search space by a large amount and that the search process should reach a final stable state more quickly. For a more complicated decision mechanism, a multi-agent simulation based on the above NK model is used to explore the effect of the two-chain organization structure on the speed, stability, and performance of the search process. The results provide three insights into how, compared with the single-chain hierarchical organization, the two-chain organization can improve the search process: it can reduce the number of iterations efficiently; the search is more stable because the search space is a smoother hill-like fitness landscape; in general, the search performance can be improved.However, when the organization structure is very complicated, the performance of a two-chain organization is inferior to that of a single-chain organization. These findings about the efficiency of the unique Chinese-style organization structure can be used to guide organization design for complex projects.
基金supported by the National Key Research and Development Program of China(2016YFB0901104)。
文摘In this paper,a theoretical framework of Multiagent Simulation(MAS)is proposed for strategic bidding in electricity markets using reinforcement learning,which consists of two parts:one is a MAS system used to simulate the competitive bidding of the actual electricity market;the other is an adaptive learning strategy bidding system used to provide agents with more intelligent bidding strategies.An ExperienceWeighted Attraction(EWA)reinforcement learning algorithm(RLA)is applied to the MAS model and a new MAS method is presented for strategic bidding in electricity markets using a new Improved EWA(IEWA).From both qualitative and quantitative perspectives,it is compared with three other MAS methods using the Roth-Erev(RE),Q-learning and EWA.The results show that the performance of the MAS method using IEWA is proved to be better than the others.The four MAS models using four RLAs are built for strategic bidding in electricity markets.Through running the four MAS models,the rationality and correctness of the four MAS methods are verified for strategic bidding in electricity markets using reinforcement learning.
基金supported in part by NSFC (62102099, U22A2054, 62101594)in part by the Pearl River Talent Recruitment Program (2021QN02S643)+9 种基金Guangzhou Basic Research Program (2023A04J1699)in part by the National Research Foundation, SingaporeInfocomm Media Development Authority under its Future Communications Research Development ProgrammeDSO National Laboratories under the AI Singapore Programme under AISG Award No AISG2-RP-2020-019Energy Research Test-Bed and Industry Partnership Funding Initiative, Energy Grid (EG) 2.0 programmeDesCartes and the Campus for Research Excellence and Technological Enterprise (CREATE) programmeMOE Tier 1 under Grant RG87/22in part by the Singapore University of Technology and Design (SUTD) (SRG-ISTD-2021- 165)in part by the SUTD-ZJU IDEA Grant SUTD-ZJU (VP) 202102in part by the Ministry of Education, Singapore, through its SUTD Kickstarter Initiative (SKI 20210204)。
文摘Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach outperforms the MAPPO approach by around 2% and effectively reduces approximately 20% of the latency of avatar task execution in UAV-assisted vehicular Metaverses.
基金supported by the National Natural Science Foundation of China(Grant Nos.42175099,42027804,42075073)the Innovative Project of Postgraduates in Jiangsu Province in 2023(Grant No.KYCX23_1319)+3 种基金supported by the National Natural Science Foundation of China(Grant No.42205080)the Natural Science Foundation of Sichuan(Grant No.2023YFS0442)the Research Fund of Civil Aviation Flight University of China(Grant No.J2022-037)supported by the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(Earth Lab)。
文摘The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.
基金supported by the National Natural Science Foundation of China(NNSFC)grants 42074202,42274196Strategic Priority Research Program of Chinese Academy of Sciences grant XDB41000000ISSI-BJ International Team Interaction between magnetic reconnection and turbulence:From the Sun to the Earth。
文摘Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas,and it is also the boundary of the solar wind energy transport to the magnetosphere.Soft X-ray imaging allows investigation of the large-scale magnetopause by providing a two-dimensional(2-D)global view from a satellite.By performing 3-D global hybrid-particle-in-cell(hybrid-PIC)simulations,we obtain soft X-ray images of Earth’s magnetopause under different solar wind conditions,such as different plasma densities and directions of the southward interplanetary magnetic field.In all cases,magnetic reconnection occurs at low latitude magnetopause.The soft X-ray images observed by a hypothetical satellite are shown,with all of the following identified:the boundary of the magnetopause,the cusps,and the magnetosheath.Local X-ray emissivity in the magnetosheath is characterized by large amplitude fluctuations(up to 160%);however,the maximum line-of-sight-integrated X-ray intensity matches the tangent directions of the magnetopause well,indicating that these fluctuations have limited impact on identifying the magnetopause boundary in the X-ray images.Moreover,the magnetopause boundary can be identified using multiple viewing geometries.We also find that solar wind conditions have little effect on the magnetopause identification.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will provide X-ray images of the magnetopause for the first time,and our global hybrid-PIC simulation results can help better understand the 2-D X-ray images of the magnetopause from a 3-D perspective,with particle kinetic effects considered.
基金support from the European Space Agency(ESA)PRODEX(PROgramme de Développement d’Expériences scientifiques)Project mission(No.PEA4000134960)Partial funding was provided by the Romanian Ministry of Research,Innovation and Digitalization under Romanian National Core Program LAPLAS VII(Contract No.30N/2023)+2 种基金the Belgian Solar-Terrestrial Centre of Excellencesupported by the project Belgian Research Action through Interdisciplinary Networks(BRAIN-BE)2.0(Grant No.B2/223/P1/PLATINUM)funded by the Belgian Office for Research(BELSPO)partially supported by a grant from the Romanian Ministry of Education and Research(CNCS-UEFISCDI,Project No.PN-III-P1-1.1TE-2021-0102)。
文摘We derived the properties of the terrestrial magnetopause(MP)from two modeling approaches,one global–fluid,the other local–kinetic,and compared the results with data collected in situ by the Magnetospheric Multiscale 2(MMS2)spacecraft.We used global magnetohydrodynamic(MHD)simulations of the Earth’s magnetosphere(publicly available from the NASA-CCMC[National Aeronautics and Space Administration–Community Coordinated Modeling Center])and local Vlasov equilibrium models(based on kinetic models for tangential discontinuities)to extract spatial profiles of the plasma and field variables at the Earth’s MP.The global MHD simulations used initial solar wind conditions extracted from the OMNI database at the time epoch when the MMS2 observes the MP.The kinetic Vlasov model used asymptotic boundary conditions derived from the same in situ MMS measurements upstream or downstream of the MP.The global MHD simulations provide a three-dimensional image of the magnetosphere at the time when the MMS2 crosses the MP.The Vlasov model provides a one-dimensional local view of the MP derived from first principles of kinetic theory.The MMS2 experimental data also serve as a reference for comparing and validating the numerical simulations and modeling.We found that the MP transition layer formed in global MHD simulations was generally localized closer to the Earth(roughly by one Earth radius)from the position of the real MP observed by the MMS.We also found that the global MHD simulations overestimated the thickness of the MP transition by one order of magnitude for three analyzed variables:magnetic field,density,and tangential speed.The MP thickness derived from the local Vlasov equilibrium was consistent with observations for all three of these variables.The overestimation of density in the Vlasov equilibrium was reduced compared with the global MHD solutions.We discuss our results in the context of future SMILE(Solar wind Magnetosphere Ionosphere Link Explorer)campaigns for observing the Earth’s MP.
基金the European Research Council for starting grant 200141-QuESpace,with which the Vlasiator model was developedconsolidator grant 682068-PRESTISSIMO awarded for further development of Vlasiator and its use in scientific investigations+4 种基金Academy of Finland grant numbers 338629-AERGELC’H,339756-KIMCHI,336805-FORESAIL,and 335554-ICT-SUNVACThe Academy of Finland also supported this work through the PROFI4 grant(grant number 3189131)support from the NASA grants,80NSSC20K1670 and 80MSFC20C0019the NASA GSFC FY23 IRADHIF funds。
文摘Solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing techniques.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)and Lunar Environment heliospheric X-ray Imager(LEXI)missions aim to obtain soft Xray images of near-Earth space thanks to their Soft X-ray Imager(SXI)instruments.While earlier modeling works have already simulated soft X-ray images as might be obtained by SMILE SXI during its mission,the numerical models used so far are all based on the magnetohydrodynamics description of the space plasma.To investigate the possible signatures of ion-kinetic-scale processes in soft Xray images,we use for the first time a global hybrid-Vlasov simulation of the geospace from the Vlasiator model.The simulation is driven by fast and tenuous solar wind conditions and purely southward interplanetary magnetic field.We first produce global X-ray images of the dayside near-Earth space by placing a virtual imaging satellite at two different locations,providing meridional and equatorial views.We then analyze regional features present in the images and show that they correspond to signatures in soft X-ray emissions of mirrormode wave structures in the magnetosheath and flux transfer events(FTEs)at the magnetopause.Our results suggest that,although the time scales associated with the motion of those transient phenomena will likely be significantly smaller than the integration time of the SMILE and LEXI imagers,mirror-mode structures and FTEs can cumulatively produce detectable signatures in the soft X-ray images.For instance,a local increase by 30%in the proton density at the dayside magnetopause resulting from the transit of multiple FTEs leads to a 12%enhancement in the line-of-sight-and time-integrated soft X-ray emissivity originating from this region.Likewise,a proton density increase by 14%in the magnetosheath associated with mirror-mode structures can result in an enhancement in the soft X-ray signal by 4%.These are likely conservative estimates,given that the solar wind conditions used in the Vlasiator run can be expected to generate weaker soft X-ray emissions than the more common denser solar wind.These results will contribute to the preparatory work for the SMILE and LEXI missions by providing the community with quantitative estimates of the effects of small-scale,transient phenomena occurring on the dayside.
基金supported in part by the National Natural Science Foundation of China (62136008,62236002,61921004,62173251,62103104)the “Zhishan” Scholars Programs of Southeast Universitythe Fundamental Research Funds for the Central Universities (2242023K30034)。
文摘Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline experience.Besides, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.
基金Ministry of Education,Singapore,under AcRF TIER 1 Grant RG64/23the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship,a Schmidt Futures program,USA.
文摘Multi-agent reinforcement learning(MARL)has been a rapidly evolving field.This paper presents a comprehensive survey of MARL and its applications.We trace the historical evolution of MARL,highlight its progress,and discuss related survey works.Then,we review the existing works addressing inherent challenges and those focusing on diverse applications.Some representative stochastic games,MARL means,spatial forms of MARL,and task classification are revisited.We then conduct an in-depth exploration of a variety of challenges encountered in MARL applications.We also address critical operational aspects,such as hyperparameter tuning and computational complexity,which are pivotal in practical implementations of MARL.Afterward,we make a thorough overview of the applications of MARL to intelligent machines and devices,chemical engineering,biotechnology,healthcare,and societal issues,which highlights the extensive potential and relevance of MARL within both current and future technological contexts.Our survey also encompasses a detailed examination of benchmark environments used in MARL research,which are instrumental in evaluating MARL algorithms and demonstrate the adaptability of MARL to diverse application scenarios.In the end,we give our prospect for MARL and discuss their related techniques and potential future applications.
基金Project supported by the National Natural Science Foundation of China(Grant No.62363005)the Jiangxi Provincial Natural Science Foundation(Grant Nos.20161BAB212032 and 20232BAB202034)the Science and Technology Research Project of Jiangxi Provincial Department of Education(Grant Nos.GJJ202602 and GJJ202601)。
文摘This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.
文摘The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in MS-Excel.Focused on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning requirements.The chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an escalation.The SS approach showed exceptional efficacy in calculating odds of failure that are notably low.Within computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO models.The ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most promising.This study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation infrastructure.These findings contribute to the enhancement of safety and reliability in real-world situations.
基金supported by the National Natural Science Foundation of China(62073019)。
文摘This paper investigates the problem of global/semi-global finite-time consensus for integrator-type multi-agent sys-tems.New hyperbolic tangent function-based protocols are pro-posed to achieve global and semi-global finite-time consensus for both single-integrator and double-integrator multi-agent systems with leaderless undirected and leader-following directed commu-nication topologies.These new protocols not only provide an explicit upper-bound estimate for the settling time,but also have a user-prescribed bounded control level.In addition,compared to some existing results based on the saturation function,the pro-posed approach considerably simplifies the protocol design and the stability analysis.Illustrative examples and an application demonstrate the effectiveness of the proposed protocols.