• Title/Summary/Keyword: Multi Agent Simulation

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Opportunistic Spectrum Access with Discrete Feedback in Unknown and Dynamic Environment:A Multi-agent Learning Approach

  • Gao, Zhan;Chen, Junhong;Xu, Yuhua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.3867-3886
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    • 2015
  • This article investigates the problem of opportunistic spectrum access in dynamic environment, in which the signal-to-noise ratio (SNR) is time-varying. Different from existing work on continuous feedback, we consider more practical scenarios in which the transmitter receives an Acknowledgment (ACK) if the received SNR is larger than the required threshold, and otherwise a Non-Acknowledgment (NACK). That is, the feedback is discrete. Several applications with different threshold values are also considered in this work. The channel selection problem is formulated as a non-cooperative game, and subsequently it is proved to be a potential game, which has at least one pure strategy Nash equilibrium. Following this, a multi-agent Q-learning algorithm is proposed to converge to Nash equilibria of the game. Furthermore, opportunistic spectrum access with multiple discrete feedbacks is also investigated. Finally, the simulation results verify that the proposed multi-agent Q-learning algorithm is applicable to both situations with binary feedback and multiple discrete feedbacks.

A Study of HEAP-based Intelligent Agent applied to Warship Combat Simulation (함정전투 시뮬레이션을 위한 HEAP 기반 지능 에이전트에 관한 연구)

  • You, Yong-Jun;Chi, Sung-Do;Kim, Jae-Ick
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.281-289
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    • 2010
  • Recently the intelligent agent systems have been emerged as one of key issues for developing the defense M&S systems. However, most conventional agent architecture of M&S systems utilize the script-based models and can only deal with the individual behaviors so that they cannot suitably describe the precise tactical/strategic behavior and/or complex warfare environment. To overcome these problems, we have proposed the HEAP(Hierarchical Encapsulation and Abstraction Principle)-based hierarchical multi-agent system architecture that is able to intelligently cope with the complex missions based on the functional role of each agent on the hierarchy such as an intelligence officer, captain, commander.

A Systolic Parallel Simulation System for Dynamic Traffic Assignment : SPSS-DTA

  • Park, Kwang-Ho;Kim, Won-Kyu
    • Journal of Intelligence and Information Systems
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    • v.6 no.1
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    • pp.113-128
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    • 2000
  • This paper presents a first year report of an ongoing multi-year project to develop a systolic parallel simulation system for dynamic traffic assignment. The fundamental approach to the simulation is systolic parallel processing based on autonomous agent modeling. Agents continuously act on their own initiatives and access to database to get the status of the simulation world. Various agents are defined in order to populate the simulation world. In particular existing modls and algorithm were incorporated in designing the behavior of relevant agents such as car-following model headway distribution Frank-Wolf algorithm and so on. Simulation is based on predetermined routes between centroids that are computed off-line by a conventional optimal path-finding algorithm. Iterating the cycles of optimization-then-simulation the proposed system will provide a realistic and valuable traffic assignment. Gangnum-Gu district in Seoul is selected for the target are for the modeling. It is expected that realtime traffic assignment services can be provided on the internet within 3 years.

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Research on Finite-Time Consensus of Multi-Agent Systems

  • Chen, Lijun;Zhang, Yu;Li, Yuping;Xia, Linlin
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.251-260
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    • 2019
  • In order to ensure second-order multi-agent systems (MAS) realizing consensus more quickly in a limited time, a new protocol is proposed. In this new protocol, the gradient algorithm of the overall cost function is introduced in the original protocol to enhance the connection between adjacent agents and improve the moving speed of each agent in the MAS. Utilizing Lyapunov stability theory, graph theory and homogeneity theory, sufficient conditions and detailed proof for achieving a finite-time consensus of the MAS are given. Finally, MAS with three following agents and one leading agent is simulated. Moreover, the simulation results indicated that this new protocol could make the system more stable, more robust and convergence faster when compared with other protocols.

A Study for Evacuation Assistance to Vulnerable People by MAS Based Evacuation Simulation (MAS 기반 대피시뮬레이션을 활용한 안전약자 대피지원 개선방안 연구)

  • Jung, Tae Ho;Park, Sang Hyun;Jang, Jae Soon
    • Journal of the Korean Society of Safety
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    • v.32 no.1
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    • pp.121-127
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    • 2017
  • Recently, many patients in a hospital are threatened life by fire disaster. Because many patients like vulnerable people have more evacuation problem than ordinary person. So a patient who can escape by oneself with walking assistance device like crutches or wheelchair and another patient who can't escape by oneself are should be supported safety technologies and service. Earlier research of 'hospital evacuation' led by actual experiments or computer evacuation simulation. Actual experiment is effective to gain credibility of result but it is difficult for patients to experiment repeatedly and it requires consideration for spatial problem and economic problems. Although computer evacuation simulation have been used to solve these problems, almost have concluded only results based on velocity without evacuation device. In this study, evacuation results with support device application or not are analysed used by computer evacuation simulation based on MAS(Multi Agent System). As a result, it is drawn through proof of efficiency of evacuation device in the vertical space like stairs that can improve the evacuation plan for vulnerable people in the hospital.

A Study for Optimal Evacuation Simulation by Artificial Intelligence Evacuation Guidance Application (인공지능 피난유도설비 적용에 따른 최적 대피시뮬레이션 연구)

  • Jang, Jae-Soon;Kong, Il-Chean;Rie, Dong-Ho
    • Journal of the Korean Society of Safety
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    • v.28 no.3
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    • pp.118-122
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    • 2013
  • For safe evacuation in the fire disaster, the evacuees must find the exit and evacuate quickly. Especially, if the evacuees don't know the location of the exit, they have to depend on the evacuation guidance system. Because the more smoke spread, the less visibility is decreasing, it is difficult to find the way to the exit by the naked eye. For theses reasons, the evacuation guidance system is highly important. However, the evacuation guidance system without change of direction has the risk that introduce to the dangerous area. In the evacuation safety assessment scenario by the evacuation simulation has the same problem. Because the evacuee in the simulation evacuate by the shortest route to the exit, the simulation result is same like the evacuation without the evacuation guidance system. In this study, it was used with MAS (Multi Agent System)-based simulation program including the evacuation guidance system to implement the change of evacuation by fire. Using this method, confidence of evacuation safety assessment can be increase.

Multi-dynamic Decision Support System for Multi Decision Problems for Highly Ill.structured Problem in Ubiquitous Computing (유비쿼터스 환경에서 다중 동적 의사결정지원시스템(UMD-DSS) : 비구조적 문제 중심으로)

  • Lee, Hyun-Jung;Lee, Kun-Chang
    • Journal of Intelligence and Information Systems
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    • v.14 no.2
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    • pp.83-102
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    • 2008
  • Ubiquitous computing requires timely supply of contextual information in order to upgrade decision quality. In this sense, this study is aimed at proposing a multi-dynamic decision support system for highly ill-structured problems. Especially, it is very important for decision makers in the ubiquitous computing to coordinate conflicts among local goals and global goal harmoniously. The proposed Multi-Dynamic Decision Support System (MDDSS) is basically composed of both central structure and distributed structure, in which central structure supports multi objects decision making and distributed structure supports individual decision making. Its hybrid architecture consists of decision processor, multi-agent controller and intelligent knowledge management processor. Decision processor provides decision support using contexts which come from individual agents. Multi-agent controller coordinates tension among multi agents to resolve conflicts among them. Meanwhile, intelligent knowledge management processor manages knowledge to support decision making such as rules, knowledge, cases and so on. To prove the validity of the proposed MDDSS, we applied it to an u-fulfillment problem system in which many kinds of decision makers exist trying to satisfy their own objectives, and timely adjustment of action strategy is required. Therefore, the u-fulfillment problem is a highly ill-structured problem. We proved its effectiveness with the aid of multi-agent simulation comprising 60 customers and 10 vehicles under three experimental modes.

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Road Networks and Crime Occurrence Multi-Agent Simulation for Smart Safe City (스마트 안전도시 조성을 위한 도로망 특성과 범죄발생 멀티에이전트(Multi-Agent) 시뮬레이션)

  • MOON, Tae-Heon;CHO, Jung-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.2
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    • pp.120-134
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    • 2015
  • Under the hypothesis that the form of road network could affect crime occurrence, this study demonstrates to prove them using Space Syntax with real crime data. We calculated integration, control, connection index by means of Space Syntax and analyzed the relationship between the three indexes and the number of crime occurrence on the each road. Next, in order to generalize the analysis results we adopted Multi-Agent Model and simulated several scenarios on the computer virtual space. The results revealed that integration index has the strongest relationship with crime occurrence both in the case of real study area and virtual space simulations. Though this study has several limitations on the extent of virtual space and realistic computer programming of agents' behavior, the results are meaningful to verify the relationship between the form of read network and crime occurrence. Moreover the simulation platform that this study developed has promising possibilities to find realistic solutions on the effective police deployment or facility layout to improve smart safe city development.

Q-learning for intersection traffic flow Control based on agents

  • Zhou, Xuan;Chong, Kil-To
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.94-96
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    • 2009
  • In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

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Agent based real-time fault diagnosis simulation (에이젼트기반 실시간 고장진단 시뮬레이션기법)

  • 배용환;이석희;배태용;이형국
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.670-675
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    • 1994
  • Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

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