• The Transactions of the Korea Information Processing Society
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• v.7 no.5S
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• pp.1687-1695
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• 2000

Recently, many researchers have tried to establish EC framework EC framework for automated contract and brokerage using agent technologies in electronic commerce. Traditional researches, however, often enforced the user's participations during the automated brokerage process of agents an did not supported the procedures and methodologies for satisfying various user's requirements. In this paper, we propose a brokerge framework based on multi-agent to overcome the defects of the previous researches. For the optimal brokerage, the proposed framework is divided into tow layers, which are called competition layer and constraint satisfaction layer. The Agents process behaviors of brokerage through two layers accroding to th proposed message driven communication protocol. W also apply CSP (Constraint Satisfaction Problems) techniques to brokerage process to satisfy various preferential requirements from the user. That is, e model the relationship between buyer agents and seller agents using CSP and propose efficient CSP models for the optimal brokerage as the types of brokerage. Finally, e implemented prototype systems applying the proposed framework and showed the efficiency of he proposed framwork with the experimental results.

• Safety and Health at Work
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• v.9 no.4
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• pp.473-478
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• 2018

Background: Multiple Chemical Sensitivity (MCS) is an acquired disease which etiology remains unknown. It is characterized by the development of sensitivity to certain chemical products. Most of the hypotheses formulated to explain the syndrome associate it to a previous exposition to some kind of volatile chemical. University researchers in chemical laboratories suffer a phenomenon of multi-exposition to chemical agents at low concentration during long periods of time although in an irregular form. Many of these chemical agents have similar properties to those suspicious of causing MCS. This article studies the prevalence of MCS in laboratory researchers. Methods: The study group is university researchers in chemical laboratories. The control group was obtained from administrative personnel who work in the same universities and therefore, are not exposed to chemical products from the laboratories, but have the same exposition to the rest of environmental polluting agents from the area and from the buildings of the university. In this study, it is used the Quick Environmental Exposure and Sensitivity Inventory (QEESI) (sensitivity of 92%/specificity of 95%). Results: The results showed that the prevalence of MCS for the university researchers is not related to exposition by inhalation to multiple chemical agents, at low concentration. Conclusions: The results disagree with one of the main etiological hypotheses of MCS, which is based on the existence of hypersensitive people, who presents a response after prolonged expositions to very low concentrations during a long period of time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.4
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• pp.3-11
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• 2003

It is very important to detect and remove original sources of various attacks through networks. One of the effective method to detect the sources is traceback systems. In this paper, we design and implement an agent-based traceback system that does not require the reaction of routers and administrators and does not need numerous log data. In the design, we introduce a traceback server and traceback agents in each network Using sniffing and spoofing, the server transmits a packet with a specific message. The agents detect the packet and provide the information for the server to trace back the original source.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.205-211
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• 2024

The purpose of this study is to implement an agent that intelligently performs tracking and movement through reinforcement learning using the Unity and ML-Agents. In this study, we conducted an experiment to compare the learning performance between training one agent in a single learning simulation environment and parallel training of several agents simultaneously in a multi-learning simulation environment. From the experimental results, we could be confirmed that the parallel training method is about 4.9 times faster than the single training method in terms of learning speed, and more stable and effective learning occurs in terms of learning stability.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.103-111
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• 2023

Consensus, that aims to converge the states of agents to the same states through information exchanges between agents, has been widely studied to control the multi-agent systems. In real systems, the measurement variables of each agent may be different, the loss of information across communication may occur, and the different networks for each state may need to be constructed for safety. Moreover, the input saturation and the disturbances in the system may cause instability. Therefore, this paper studies the PID(Proportional-Integral-Derivative)-based consensus control to achieve the swarm behavior of the multi-agent systems considering the heterogeneous state information, the input saturations, and the disturbances. Specifically, we consider the multiple follower agents and the single leader agent modeled by the second-order systems, and investigate the conditions to achieve the consensus based on the stability of the error system. It is confirmed that the proposed algorithm can achieve the consensus if only the connectivity of the position graph is guaranteed. Moreover, by extending the consensus algorithm, we study the formation control problem for the multi-agent systems. Finally, the validity of the proposed algorithm was verified through the simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.8-13
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• 2008

This paper presents auto-reclosing algorithms with reference to power system stability based on MAS(Multi-Agent System). And this paper shows auto-reclosing algorithms considering power system stability. It includes the variable dead time, optimal reclosing, sequential reclosing, emergency extended equal-area criterion(EEEAC) algorithm, and modified EEEAC algorithm. This paper divides Auto-reclosing algorithms into respectively agents according to their tasks. A separated agent is merely a software entity that is situated in some environment and is able to autonomously react to changes in the environment. And all the simulations in this parer were tested by EMTP MODELS.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.149.1-149
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• 2001

In multi robot environment, the action selection strategy is important for the cooperation and coordination of multi agents. However the overlap of actions selected individually by each robot makes the acquisition of cooperation behaviors less efficient. In addition to that, a complex and dynamic environment makes cooperation even more difficult. So in this paper, we propose a control algorithm which enables each robot to determine the action for the effective cooperation in multi-robot system. Here, we propose cooperative algorithm with reinforcement learning to determine the action selection In this paper, when the environment changes, each robot selects an appropriate behavior strategy intelligently. We employ ...

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.1-17
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• 2005

Agent technology has been widely applied in today's electronic business, such as mobile agents, multi-agent information systems, etc. In particular, multi-agent systems have been applied as powerful simulation tools to study complex business networks composed of various self-interested trading firms and/or human beings. In this paper, we build an integrated model that consists of a multi-agent B2C market model and a B2B trade network model, and incorporate more reality than much of prior work. Then with this model, we carry out experimental studies on two different strategies that are common in electronic business - 'loyal' strategy (retailers try to build stable cooperation with suppiers to ensure material supply) and 'cost-saving' strategy (retailers try to reduce cost by choosing suppliers with lower wholesale price).

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.299-301
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• 2003

In this paper, a protection system using Multi-Agent concept for power distribution network is proposed. Multi agent system consist of Feeder agent, OCR(Over Current Relay) agent, Recloser agent and Switch agent. An agent calculates and corrects its parameter by itself through communication with neighboring agents and its own intelligence algorithm. Simulations in a simple distribution network show the effectiveness of the suggested protection system. Multi-Agent System, protection of distribution network, Communication.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.507-512
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• 1998

It is an interesting area in the field of artificial intelligence to and an analytic model of cooperative structure for multi-agent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent co-operative behavior: A modified genetic algorithm was applied to automating the discovery of a fuzzy logic controller jot multi-agents playing a pursuit game. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to and the fuzzy logic controller seems to be promising.