• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.661-664
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• 2000

본 연구에서는 인터넷을 기반으로 하고 GIS(Geographical Information System)와 ITS(Intelligent Transportation System)제어 응용을 고려 한 컴퓨팅 플랫폼으로 EIMAS(Efficient and Intelligent Multi-Agent System)을 제안한다. GIS 와 관련 활용 시스템들은 개방형 지리 정보 처리 상호 운용 개념이 확산되면서 물리적으로 분산된 환경을 가지지게 되었고 이러한 분산 환경에서 프로그램개발과 사용자의 요구에 서비스를 효과적으로 제공하기 위하여, GIS와 이와 연계한 GI(Geographical Information) 활용시스템들의 각기 다른 구성 요소들을 통합하는 시스템이 요구된다. GIS 와 GIS Application으로 ITS(Intelligent Transportation System)위한 Java Mobile Agent와 Multiple Agent System 인 EIMAS를 플렛폼으로 제안한다. 이 시스템은 GIS 시스템과 ITS 시스템에 제공되는 Agent가 활동하는 플레이스 위에서 에이전트가 목적과 워크에 적합한 효율적인 워크플로우를 생성하여 시간 효율적이고 지능적인 분산. 병렬처리를 수행하는 플렛폼을 설계한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.269-279
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• 1999

본 연구는 Web상에서 원격 협력 학습을 위한 수준별 학습자 모집 스케줄링 에이전트의 설계와 구현에 관해 제안한다. 본 시스템의 구조는 원격 교사 모듈과 여러 명의 학습자, 그리고 이를 연결해 주는 스케줄링 Agents, 학습자를 진단할 수 있는 진단 Agent로 구성된다. 컴퓨터가 분산환경으로 발전됨에 따라서 교육의 변화도 가속화되었고, 지식의 공유와 정보의 공유가 원격 협력학습에 의하여 절실히 필요하게 되었다. 원격 협력 학습에서의 학습자는 동일한 과목과 주제에 흥미를 느끼는 여러 명의 아동이 동시에 학습할 수 있는 상황이 필요하며, 선행 지식 또한 비슷한 수준이어야 동일한 주제로 학습의 효과가 있다. 이런 학습자를 판단하기 위해서 진단 Agent가 학습자를 진단하며 스케줄링 Agents의 학습자 지식에 추가한 후 스케줄링 Agents가 학습자의 기본 사항과 요구 내용을 추론하여 비슷한 수준의 학습자를 연결한다. 교사 모듈은 전통적인 ITS의 구조의 교수 학습 모듈, 전문가모듈로 구성되어 교수 학습을 할 수 있다. 이렇게 여러 명의 학습자를 연결하여 협력학습을 하기 위해서는 학습자간의 요구사항과 지식 수준 그리고 학습 가능한 시간이 같아야 하는데 이를 위해 시간을 자원으로 하는 동적 자원 스케줄링(Dynamic Resource Scheduling)으로 모델링 하였다. 본 연구에서 도형학습을 기반으로 하는 실험을 통해 구현한 원격 협력학습을 위한 지능형 스케줄링 에이전트를 평가하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.457-467
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• 2004

In this paper, a robot is considered as an agent, a structure of robot is presented which consisted by multi-subagents and they have diverse capacity such as perception, intelligence, action etc., required for robot. Also, subagents are consisted by micro-agent($\mu$agent) charged for elementary action required. The structure of robot control have two sub-agents, the one is behavior based reactive controller and action selection sub agent, and action selection sub-agent select a action based on the high label action and high performance, and which have a learning mechanism based on the reinforcement learning. For presented robot structure, it is easy to give intelligence to each element of action and a new approach of multi robot control. Presented robot is simulated for two goals: chaotic exploration and obstacle avoidance, and fabricated by using 8bit microcontroller, and experimented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.3
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• pp.322-331
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• 2013

This paper describes the development of the pilot plant of distributed intelligent management system for a microgrid. For optimal control and management of microgrids, intelligent agents area applied to the microgrid management system. Each agent includes intelligent algorithms to make decisions on behalf of the corresponding microgrid entity such as distributed generators, local loads, and so on. To this end, each agent has its own resources to evaluate the system conditions by collecting local information and also communicating with other agents. This paper presents key features of the data communication and management of the developed pilot plant such as the construction of mesh network using local wireless communication techniques, the autonomous agent coordination schemes using plug-and-play functions of agents and contract net protocol (CNP) for decision-making. The performance of the pilot plant and developed algorithms are verified via real-time microgrid test bench based on hardware-in-the-loop simulation systems.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.712-717
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• 2007

Using home network system including home server, home service robot, a variety of device, it is generally known that application of Multi Agent System for performing variously distributed process that can be occur in home environment, is efficient method. In this system, it is intelligent service robot that a key of human interface and physical service offer Therefore, using application of established multi agent system, we can defined Multi Agent Robot System. In 'open' home environment, between all agent data interaction and cooperation are needed for Multi Agent System offer to user that more efficient service. For this, we focus our attention on define as agent that can autonomic drive and offer to user that physical service robots and, design, suggest the simulator can display that between robot agents communication or between other agents, like home server, and robot agents communication information to user interface.

• 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 Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.445-454
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• 2000

의료 정보 시스템은 많은 지식과 의료 인력과의 연계가 필요하기 때문에, 멀티 에이전트 시스템의 활용 영역으로 적합하다. 본 논문에서는 지능형 의료 정보 제공을 위한 멀티 에이전트 시스템인 MAMI(Multi-Agent system for Medical Image)의 에이전트 플랫폼의 설계 및 구현 대해 기술한다. MAMI는 여러 의료 정보 중 의료 영상을 위한 멀티 에이전트 시스템이다. MAMI의 가장 중요한 구성 요소로서는 에이전트 플랫폼을 들 수 있다. 에이전트 플랫폼은 에이전트들이 동작할 수 있는 물리적 기반을 제공해 준다. MAMI는 FIPA(foundation for Intelligent Physical Agent)가 제안하는 관리 모델을 따르고 있다. MAMI에서는 COM(Common Object Model)과 XML(Extensible Markup Language)로 인코딩된 ACL(Agent Communication Language)을 메시지 교환에 이용하고 있다. 의료 영역의 특성상 의사와 같은 의료 전문 인력과의 연계는 반드시 필요하다. MAMI는 이를 위해서 의료 인력을 하나의 에이전트로 개념화하여 시스템에 연결한다. MAMI의 에이전트 플랫폼은 소프트웨어 에이전트와 휴먼 에이전트들이 지식을 공유하기에 적합한 물리적 기반을 제 공해주어 지능형 의료 정보 서비스를 용이하게 해준다.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1062-1072
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• 2006

Recently, new intelligent service frameworks, such as ubiquitous computing are proposed. So, the necessity of adaptive agent system has been increased. In this paper, we propose an intelligent service agent to help that ubiquitous computing system offer user suitable service in ubiquitous computing environment. In order to offer user suitable uT-service, an intelligent service agent mediates the gap between the context information in uT-service system, and user preference is reflected in it. Therefore, we focus on following three components; the first is suitable multi agent framework-agent communication analysis and applicable method of inference engine, the second is uT-ontologies to describe various context information-context information sharing between agents and context information understanding between agents, the third is learning method of user profile to apply in uT-service system. This approach enables us to build adaptive uT-service system to offer suitable service according to user preference.

• 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.