Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune s...Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.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 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
The delegation-agent models in agricultural insurance are established both under the circumstances of information symmetry and information asymmetry.Insurers choose effort level-a* according to the first order optimal...The delegation-agent models in agricultural insurance are established both under the circumstances of information symmetry and information asymmetry.Insurers choose effort level-a* according to the first order optimal condition of ∫{v(π-s(π))+λ11[u(s(π))]fa(π,a*)}dπ=λ11c'(a*)u(s(π)) at the present stage when the information is symmetric.While the information is asymmetric,the first order optimal condition changed into v'(π-s(π))u'(s(π))=λ21+μ21(1-fa(π,a)f(π,a)).In other words,the higher the output,the more and more income of insured.The paper also modifies the models,when the information is symmetric,the insurers determine the effort level of insured-a* based on the first order optimal condition of ∫{v(π-s(π))+λ12[u(s(π))]fa(π,a*)}dπ=λ12h'(a*)u(s(π));to the contrary,the first order optimal condition would change into v'(π*-s(π*))u'(s(π*))=λ22+μ22(1-fa(π,a)f(π,a))-λh(a)f(π,a)-μh'(a)f(π,a).The results show that the insured and the insurers would both benefit from the insurance when the effort cost function related to the expectation of the insured(agricultural producers).If the insured manage the objects of insurance more seriously,the rate of disasters would be lowered.Therefore,the insurance claimed against the insured would be lessened,and the benefits of the insurers would be increased at last.展开更多
In this paper,the multi-agent model about shop logistics is set up. This model has 8 agents: raw materials stock agent,process agent,testing agent,transition agent,production information agent,scheduling agent,process...In this paper,the multi-agent model about shop logistics is set up. This model has 8 agents: raw materials stock agent,process agent,testing agent,transition agent,production information agent,scheduling agent,process agent and stock agent. The scheduling agent has three subagents: manager agent (MA),resource agent (RA) and part agent (PA). MA,PA and RA are communicating equally that guarantees agility of the whole MAS system. The part tasks pass between MA,RA and PA as an integer,which can guarantee the consistency of the data. We use a detailed example about shop logistics scheduling in a semiconductor company to explain the principle. In this example,we use two scheduling strategies: FCFS and SPT. The result data indicates that the average flow time and lingering ratio are changed using different strategy. It is proves that the multi-agent scheduling is useful.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
One of the main objectives of artificial intelligence lies in the simulation of the behavior of living organisms;emotions are a fundamental part of life, and they cannot be left aside when simulating behavior. In this...One of the main objectives of artificial intelligence lies in the simulation of the behavior of living organisms;emotions are a fundamental part of life, and they cannot be left aside when simulating behavior. In this research, software is developed that simulates the behavior of birds with different characteristics. The latter interacts by considering different stimuli from the environment (external), and the internal state of the subject (objectives). To achieve this, a model of birds in the role of prey and predators is developed that focuses on the study of the interaction between these organisms that exhibit specific behaviors in their environment. This project is a seminal work that aims to represent the emotions of birds, and the latter caused by stimuli from a dynamic environment.展开更多
文摘Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.
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The delegation-agent models in agricultural insurance are established both under the circumstances of information symmetry and information asymmetry.Insurers choose effort level-a* according to the first order optimal condition of ∫{v(π-s(π))+λ11[u(s(π))]fa(π,a*)}dπ=λ11c'(a*)u(s(π)) at the present stage when the information is symmetric.While the information is asymmetric,the first order optimal condition changed into v'(π-s(π))u'(s(π))=λ21+μ21(1-fa(π,a)f(π,a)).In other words,the higher the output,the more and more income of insured.The paper also modifies the models,when the information is symmetric,the insurers determine the effort level of insured-a* based on the first order optimal condition of ∫{v(π-s(π))+λ12[u(s(π))]fa(π,a*)}dπ=λ12h'(a*)u(s(π));to the contrary,the first order optimal condition would change into v'(π*-s(π*))u'(s(π*))=λ22+μ22(1-fa(π,a)f(π,a))-λh(a)f(π,a)-μh'(a)f(π,a).The results show that the insured and the insurers would both benefit from the insurance when the effort cost function related to the expectation of the insured(agricultural producers).If the insured manage the objects of insurance more seriously,the rate of disasters would be lowered.Therefore,the insurance claimed against the insured would be lessened,and the benefits of the insurers would be increased at last.
基金Supported by the Zhejiang Province Science Foundation of China( M703022)
文摘In this paper,the multi-agent model about shop logistics is set up. This model has 8 agents: raw materials stock agent,process agent,testing agent,transition agent,production information agent,scheduling agent,process agent and stock agent. The scheduling agent has three subagents: manager agent (MA),resource agent (RA) and part agent (PA). MA,PA and RA are communicating equally that guarantees agility of the whole MAS system. The part tasks pass between MA,RA and PA as an integer,which can guarantee the consistency of the data. We use a detailed example about shop logistics scheduling in a semiconductor company to explain the principle. In this example,we use two scheduling strategies: FCFS and SPT. The result data indicates that the average flow time and lingering ratio are changed using different strategy. It is proves that the multi-agent scheduling is useful.
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.
文摘One of the main objectives of artificial intelligence lies in the simulation of the behavior of living organisms;emotions are a fundamental part of life, and they cannot be left aside when simulating behavior. In this research, software is developed that simulates the behavior of birds with different characteristics. The latter interacts by considering different stimuli from the environment (external), and the internal state of the subject (objectives). To achieve this, a model of birds in the role of prey and predators is developed that focuses on the study of the interaction between these organisms that exhibit specific behaviors in their environment. This project is a seminal work that aims to represent the emotions of birds, and the latter caused by stimuli from a dynamic environment.
