• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.120-125
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• 2000

SNMP(Simple Network Management Protocol) could have the overhead of network, if the number of the agent system which is managed by the management system is increased by the polling for the collection of network management information and the reply traffic for it. In this Paper, the polling method used in SNMP is improved, and Group Polling method is proposed. This can reduce the overhead of network, on case that the agent system is to be increased. The proposed method collects information by grouping agent systems, and have smaller reply latency time and communication overhead than the previous method. So if the number of agent system or the Polling count is numerous, the proposed method is more efficient. As the result of the prototype test, the increasement of agent system can have small variation of traffic and transmission delay time.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.69-78
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• 2015

Recently, research on the multi-agent system is developed actively in the various fields, especially on the control of complex system and optimization. In this study, we develop a multi-agent system for NPC simulation in game environment. The purpose of the development is to support quick and precise decision by inferencing the situation of the dynamic discrete domain, and to support an optimization process of the agent system. Our approach employed Petri-net as a basic agent model to simplify structure of the system, and used fuzzy inference engine to support decision making in various situation. Our experimentation describes situation of the virtual battlefield between the NPCs, which are divided two groups, such as fuzzy rule based agent and automata based agent. We calculate the percentage of winning and survival rate from the several simulations, and the result describes that the fuzzy rule based agent showed better performance than the automata based agent.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.45-49
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• 2006

홈네트워크 시스템의 본격적인 보급과 함께 가정용서비스 로봇의 최근 연구 성과들은 인간과 지능로봇이 가정에 공존하며 서로 의사소통을 할 수 있는 시대가 가까운 미래에 현실화 될 수 있음을 보여주고 있다. 그러나 가정의 환경적인 특징은 open되어 있기 때문에 그러한 환경에 적응하고 주어진 임무를 수행하는 데는 단일 로봇 또는 단일 홈서버 보다는 로봇을 포함하는 홈네트워크 시스템 내의 여러 장치들이 어울려 분산처리를 수행하는 multi-agent 시스템이 일반적으로 더 좋다고 알려져 있다. 따라서 본 논문은 홈네트워크 시스템 환경에서 가정에서 필요한 agent들을 정의하기 위한 framework 모델을 구축하고 각 agent 간의 통신 protocol architecture를 제시한다. 또한 로봇 또는 홈서버의 단일 지능이나 기능보다는 그 안에 존재하는 복수개의 agent instance들의 집합으로 agent를 정의하고 각 agent 내외에서 agent들 사이의 협력(cooperation)과 (타협)negotiation을 통해 환경과 적응하는 방법 및 사람과 교감(interactive)하는 방법을 제시한다.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.125-131
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• 2005

Service restoration is one of the most important missions in distribution system operation. This paper proposes a multi-agent system approach to distribution system restoration. Every relay is developed as an agent by adding its own intelligent, self-tuning and communication ability. The relay agent independently calculates and corrects its restoration index through communication with neighboring agents and its own intelligence. The proposed algorithm is applied to a simple network to demonstrate its soundness and effectiveness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.20-30
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• 2006

Due to recent growing interest in autonomous software agents and their potential application in areas such as electronic commerce, the autonomous negotiation become more important. Evidence from both theoretical analysis and observations of human interactions suggests that if decision makers have prior information on opponents and furthermore learn the behaviors of other agents from interaction, the overall payoff would increase. We propose a new methodology for a strategy finding process using data mining in autonomous negotiation system; ANSIA(Autonomous Negotiation System using Intelligent Agent). ANSIA is a strategy based negotiation system. The framework of ANSIA consists of three component layers; 1) search agent layer, 2) data mining agent layer and 3) negotiation agent layer. ANSIA is motivated by providing a computational framework for negotiation and by defining a strategy finding model with an autonomous negotiation process.

• Proceedings of the KIEE Conference
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• summer
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• pp.403-405
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• 2004

A service restoration is one of the most important missions in distribution system operation. This paper proposes a multi-agent system approach to distribution system restoration. Every relay is developed as an agent by adding its own intelligent, self-tuning and communication ability. Relay agent calculates and corrects its restoration index by itself through communication with neighboring agents and its own intelligence. The proposed algorithm is applied to a simple network to show how to calculate restoration index. Keywords Multi-Agent System, Service Restoration, Distribution Networks

• Journal of the Korean Society for Railway
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• v.10 no.3 s.40
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• pp.350-354
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• 2007

Intelligent agent is to decide what customers need on the internet and offer them accurate information. In this paper, the system which can recommend the tourism items in terms of customer‘s needs is proposed by appling the intelligent agent to railway tourism system. Most of previous agents are focused on price. But, this study proposes the Railway tourism system which offers each customer the best suitable information based on quality of information and reputation. The customer's needs are analyzed through intelligent agent and the information which is suitable for customer's needs is obtained the Artificial Neural Network Model.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.181-188
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• 2022

An intelligent distributed multi-agent system (IDMS) using reinforcement learning (RL) is a challenging and intricate problem in which single or multiple agent(s) aim to achieve their specific goals (sub-goal and final goal), where they move their states in a complex and cluttered environment. The environment provided by the IDMS provides a cumulative optimal reward for each action based on the policy of the learning process. Most actions involve interacting with a given IDMS environment; therefore, it can provide the following elements: a starting agent state, multiple obstacles, agent goals, and a cluttered index. The reward in the environment is also reflected by RL-based agents, in which agents can move randomly or intelligently to reach their respective goals, to improve the agent learning performance. We extend different cases of intelligent multi-agent systems from our previous works: (a) a proposed environment-clutter-based-index for agent sub-goal selection and analysis of its effect, and (b) a newly proposed RL reward scheme based on the environmental clutter-index to identify and analyze the prerequisites and conditions for improving the overall system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.268-271
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• 2003

In this paper, we propose a new framework based on negotiatory mobile multi agent system, and implement a mobile multi agent environment based on DECAF(Distributed Environment-Centered Agent Framework) which is one of the distributed agent development toolkit so as to implement a new PDS(Personal Digital Library System). The new framework has some optimality and higher performance in distributed environments.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.183-185
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• 2000

본 논문에서는 SNMP를 이용한 Nerwork Management System(NMS)이 Network을 사용하는 Application에 영향을 주지 않도록 하는 Polling 전략과 Model을 설계하였다. 제안된 System은 Network의 각 Client 정보를 처리하는 Agent와 Data 수집 및 제어를 담당하는 Server로 구성된다. Agent는 SNMP Agent 부분과 Network 상태를 Monitoring 하는 SubManager로 구성되어, Server는 SNMP Agent와의 Polling 및 Polling 정책을 결정하는 부분으로 구성된다. 제안 Model은 SNMP를 이용한 NMS를 도입할 경우, 기존 Network Service에 영향을 주지 않도록 하는 것이 목적이다. 제안된 System에 대한 성능평가를 위해 실존하는 Network을 대상으로 SNMP의 Polling 및 Service의 부하량을 측정하였다.