Multi-agent Based Hierarchy Simulation Models of Carrier-based Aircraft Catapult Launch

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.

Discrete decision model and multi-agent simulation of the Liang Zong two-chain hierarchical organization in a complex project

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.

A Fundamental Study on Multi-agent Pedestrian Model Based on Risk Avoidance Behavior during Road Blockage and Evacuation Simulation of Regional Urban Disaster

Regional cities in Japan are at the risk of experiencing big fire accidents or earthquakes every day.However,neither the number nor the capacity of shelters has increased because local governments might not consider them owing to budget shortfall.By contrast,wide-area evacuation simulations can easily provide an antagonizing image of regional urban disasters.After a disaster,the city collapses and the evacuation routes are closed;consequently,evacuees feel anxious and they cannot move as usual.This anxiety behavior has not been considered in previous related studies and simulations.In this study,a wide-area evacuation simulation is developed;this model can not only calculate the possibility of blocking escape routes when the city is broken but also provide safe and more realistic evacuation plans before a disaster occurs by incorporating into the simulation the risk avoidance behaviors of evacuees from road blockage,such as“the route re-seeking behavior”and“the shelter re-selecting behavior”.

Evaluation of Behavior of Evacuees on a Floor in a Disaster Situation Using Multi-agent Simulation and Mixed Reality Game： Effectiveness of the Field of Vision and Priority of Referred Objects

In this study, we develop a mixed reality game system to investigate characteristics ofjudgrnents of individual players in an evacuation process. The characteristics of judgments of the players that are inferred from the performance of the game are then incorporated into a multi-agent simulation as rules. The behavior of evacuees is evaluated in approximations of real situations, by using the agent simulation including different judgments of evacuees. Using the results of the simulation, effective methods are discussed for achieving the escape of the evacuees within a short time.

Evaluation of the Behavior of Evacuees on Dynamic Floor Condition by Using Multi-agent Simulation

The prediction of the behavior of people in a disaster has a useful role to play in the design of urban structures such as department stores, schools, and office buildings. We focus on using emergency exit signs to effectively guide the evacuation of people on a floor with a dynamically changing layout. A multi-agent simulation is developed to simulate the behavior of evacuees on a floor. A mathematical model is constructed to obtain optimal sign locations to efficiently assist evacuation under the condition that obstacles are dynamically generated on the floor. The optimal sign locations are calculated by the mathematical model. Then, the developed simulation is performed to evaluate the effectiveness of the emergency exit signs and the behavior of evacuees on simple layout models using the calculated optimal sign locations.

Efficient Origin-Destination Estimation Using Microscopic Traffic Simulation with Restricted Rerouting

Traffic simulators are utilized to solve a variety of traffic-related problems.For such simulators,origin-destination(OD)traffic volumes as mobility demands are required to input,and we need to estimate them.The authors regard an OD estimation as a bi-level programming problem,and apply a microscopic traffic simulation model to it.However,the simulation trials can be computationally expensive if full dynamic rerouting is allowed,when employing multi-agent-based models in the estimation process.This paper proposes an efficient OD estimation method using a multi-agent-based simulator with restricted dynamic rerouting to reduce the computational load.Even though,in the case of large traffic demand,the restriction on dynamic rerouting can result in heavier congestion.The authors resolve this problem by introducing constraints of the bi-level programming problem depending on link congestion.Test results show that the accuracy of the link traffic volume reproduced with the proposed method is virtually identical to that of existing methods but that the proposed method is more computationally efficient in a wide-range or high-demand context.

Assessing the Carrying Capacity of Tourist Resorts: An Application of Tourists’ Spatial Behavior Simulator Based on GIS and Multi-Agent System

Based on the study of visitors' individual spatial behaviors, a tourists'spatial behavior simulator (TSBS) to assess the carrying capacity of tourist resorts was developed,TSBS employs GIS (Geographic Information System) to manage the spatial data,and Multi-Agent systemto simulate the actions of individual visitors. By utilizing TSBS, visitors' travel patterns such aslocation, cost, and state can be analyzed and predicted. Based on this analysis and prediction, themodel of assessing the carrying capacity of resorts is built. Our results show that TSBS will be aneffective tool to accurately assess the carrying capacity of tourist resorts.

Distributed Intelligent Microgrid Control Using Multi-Agent Systems

In the future, the individual entities of microgrids such as distributed generators and smart loads may need to determine their power generation or consumption in more economic ways. Intelligent agents can help the decision-making procedure of the entities by intelligent algorithms and state-of-the-art communication with central controller and other local agents. This paper presents the development of atable-top microgrid control system using multi-agent systems and also the demonstration of demand response programs during power shortage. In our table-top system, agents are implemented using microcontrollers and Zigbee wireless communication technology is applied for efficient data communication in the multi-agent system. The power system models of distributed generators and loads are implemented in the real-time simulator using Opal-RT system. The whole test system that includes real-time system simulation and agent hardware is implemented in the hardware-in-the-loop simulation framework. The performance of the developed system is tested for emergency demand response cases.

Multi-agent Simulation for Strategic Bidding in Electricity Markets Using Reinforcement Learning

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.

TRISim:A Triage Simulation System to Exploit and Assess Triage Operations for Hospital Managers-Development,Validation and Experiment

Triage is a method for determining the priority of patients’treatment to improve survival rates.Different triage methods are used in hospitals,and they are applied after performing an evaluation based on standard methods such as the Japan Triage Acuity Scale(JTAS)or Emergency Severity Index(ESI).It is important to consider the characteristics of all the hospitals when assigning triage methods and emergency levels to them;the hospital managers make these decisions.We propose a multi-agent simulation method to support the hospital managers in employing the triage protocols according to their environment.We developed a prototype simulation system called TRISim to explore and assess the triage operations.In this paper,we provide an overview of TRISim and present our experimental results to validate the system.

Currency-based Iterative Multi-Agent Bidding Mechanism Based on Genetic Algorithm

This paper introduces a multi-agent system which i nt egrates process planning and production scheduling, in order to increase the fle xibility of manufacturing systems in coping with rapid changes in dynamic market and dealing with internal uncertainties such as machine breakdown or resources shortage. This system consists of various autonomous agents, each of which has t he capability of communicating with one another and making decisions based on it s knowledge and if necessary on information provided by other agents. Machine ag ents which represent the machines play an important role in the system in that t hey negotiate with each other to bid for jobs. An iterative bidding mechanism is proposed to facilitate the process of job assignment to machines and handle the negotiation between agents. This mechanism enables near optimal process plans a nd production schedules to be produced concurrently, so that dynamic changes in the market can be coped with at a minimum cost, and the utilisation of manufactu ring resources can be optimised. In addition, a currency scheme with currency-l ike metrics is proposed to encourage or prohibit machine agents to put forward t heir bids for the jobs announced. The values of the metrics are adjusted iterati vely so as to obtain an integrated plan and schedule which result in the minimum total production cost while satisfying products due dates. To deal with the optimisation problem, i.e. to what degree and how the currencies should be adj usted in each iteration, a genetic algorithm (GA) is developed. Comparisons are made between GA approach and simulated annealing (SA) optimisation technique.

Development of Simulation Tool Orienting Production Engineering

A simulation tool named BITSIM orienting production engineering is developed in order to improve enterprise＇s productivity and making up the scarcity of computer application. The architecture of BITSIM is presented first. Hierarchical technique, control strategy based on multi-agent and simulation output analysis are depicted in detail then. In the end, an application example is taken out to prove that this system could be used to analyzing different hypothetical situation and configuring the auxiliary manufacturing system before production.

Social Simulation for Analyzing Product Recall Systems Using Co-Evolution Model with Price Competition

In recent years,accidents and product recalls caused by product defects have become important problems in numerous industries worldwide.Nevertheless,most existing studies have examined product recalls using empirical approaches.To improve product recall systems,we studied social simulation using a multi-agent system with a co-evolution model.This research is important because empirical approaches are no longer adequate for complex and diverse modern societies.Discussions using quantitative and predictive approaches,including agent-based simulation,are therefore expected.For this study,we used a Layered Co-evolution Model to reflect situations of the real society using producer agents and consumer agents.Additionally,we applied multi-objective optimization techniques to introduce price competition situations into an artificial society.We conducted a simulation experiment,from which we discovered the possibilities that cost reduction for huge-scale product recalls is efficient,and that punishment of producers that conduct no product recalls can benefit consumers.We believe this work can contribute to supporting not only government staff for improving product recall systems,but also executive officers of product companies for deliberating their strategies of recall decisions.

Simulation study on the security of consensus algorithms in DAG-based distributed ledger

Due to the advantages of high volume of transactions and low resource consumption,Directed Acyclic Graph(DAG)-based Distributed Ledger Technology(DLT)has been considered a possible next-generation alternative to blockchain.However,the security of the DAG-based system has yet to be comprehensively understood.Aiming at verifying and evaluating the security of DAG-based DLT,we develop a Multi-Agent based IOTA Simulation platform called MAIOTASim.In MAIOTASim,we model honest and malicious nodes and simulate the configurable network environment,including network topology and delay.The double-spending attack is a particular security issue related to DLT.We perform the security verification of the consensus algorithms under multiple double-spending attack strategies.Our simulations show that the consensus algorithms can resist the parasite chain attack and partially resist the splitting attack,but they are ineffective under the large weight attack.We take the cumulative weight difference of transactions as the evaluation criterion and analyze the effect of different consensus algorithms with parameters under each attack strategy.Besides,MAIOTASim enables users to perform largescale simulations with multiple nodes and tens of thousands of transactions more efficiently than state-of-the-art ones.

Analysis of Commuting Modal Shift in Consideration of Social Interaction of Consciousness for Environment

It is the matter for achievement of the low carbon transport system that the excessive use of private vehicles can be controlled appropriately.Not only improvement of service level of modes except private vehicle,but also consciousness for environmental problem of individual trip maker is important for eco-commuting promotion.On the other hand,consciousness for environment would be changed by influence of other person.Accordingly,it is aimed in the study that the structure of decision-making process for modal shift to the eco-commuting mode in the local city is described considering environmental consciousness and social interaction.For the purpose,the consciousness for the environment problem and the travel behavior of the commuter at the suburban area in the local city are investigated by the questionnaire survey.The covariance structure about the eco-consciousness is analyzed with the database of the questionnaire survey by structural equation modeling.As the result,it can be confirmed with the structural equation model that the individual environmental consciousness is strongly related with the intention of self-sacrifice and is influenced with the local interaction of the individual connections.On the other hand,the intention of modal shift for the commuting mode is analyzed with the database of the questionnaire survey.It can be found out that the environmental consciousness is not statistically significant for commuting mode choice with the present poor level of service of public transport.However,the intention of self-sacrifice for the prevention of the global warming is statistically confirmed as the factor of modal shift with the operation of eco-commuting bus service with the RP/SP integrated estimation method.As the result,the multi-agent simulation system with social interaction model for eco consciousness is developed to measure the effect of the eco-commuting promotion.For the purpose,the carbon dioxide emission is estimated based on traffic demand and road network condition in the traffic environment model.On the other hand,the relation between agents is defined based on the small world network.The proposed multi-agent simulation is applied to measure the effect of the eco-commuting promotion such as improvement of level of service on the public transport or education of eco-consciousness.The effect of the promotion plan can be observed with the proposed multi-agent system.Finally,it can be concluded that the proposed multi-agent simulation with social interaction for eco-consciousness is useful for planning of eco-commuting promotion.

Networked Control System Simulation Design and Its Application

This paper presents a framework for networked control system simulation （NCSS） to enable the analysis of the influence of network transmissions on the performance of control systems. The simulation is composed of the network environment simulated using the network simulator, the control system component simulation using Matlab or C/C＋＋, and an external application programming interface. To implement the plant （sensor）, controller, and actuator nodes, an agent-based design is introduced, and a multi-agent networked control system is constructed. Therefore, the network simulator 2-26 （NS-2.26） release is extended by modifying the user data protocol （UDP） common header in order to support application data transmission between network nodes. Then, modifying the network topology parameters, networked control system simulations are analyzed for different parameter changes, such as the network bandwidth, the number of plant nodes, and the sampling period. An analysis of the influence of these parameters on network-induced delays and packet drop is made. The results show that the simulation system is an effective tool for the study of networked control systems.

Generative computer simulation for parallel layout of multi-story row house cluster

This study has established the functions between the environmental conditions and the inhabitants’ preferences for multi-story row house cluster with parallel layout, based on the data from the questionnaires’ in Beijing. A program has been written with multi-agent system and generative computer simulation approaches. The emergence candidate layout plans can be referenced and chosen by architects.

Symbiosis Analysis on Industrial Ecological System

Industrial ecological system is a sustainable mode of modern industry development. Industrial symbiosis, a sub-field of industrial ecology, engages traditionally separate industries in a collective approach, involving exchange of materials, energy, water, and/or by-products, to enhance competitive ability and environmental performance. To construct a symbiosis analysis method, this article employs a number of parameters embodying information about materials, energy and economics as the main essential parameters in system analysis and introduces symbiosis profit and symbiotic consumption elements as the economic indicators. A modeling and simulation program is designed using the agent-based modeling approach to simulate the evolvement of a hypothetical coal-based industrial system and the change of symbiosis conditions in the process of construction is examined. The simulation program built using the Swarm library, which is a freely available multi-agent simulation package, provides a useful demonstration for the symbiosis analysis method.

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

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