• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.1-11
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• 1999

Agent-based systems technology has generated lots of excitement in these years because of its promise as a new paradigm for conceptualizing. designing. and l implementing software systems Especially, there has been many researches for multi agent system because of the characteristics that it fits to the distributed and open Internet environments. In a multiagent system. agents must cooperate with each other through a Coordination procedure. when the conflicts between agents arise. where those are caused b by the point that each action acts for a purpose separately without coordination. But P previous researches for coordination methods in multi agent system have a deficiency that they can not solve correctly the cooperation problem between agents which have different goals in dynamic environment. In this paper. we solve the cooperation problem of multiagent that has multiple goals in a dynamic environment. with an automatic cooperative coordination model using I reinforcement learning. We will show the two pursuit problems that we extend a traditional problem in multi agent systems area for modeling the restriction in the multiple goals in a dynamic environment. and we have verified the validity of the proposed model with an experiment.

• The Journal of Engineering Research
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• v.7 no.1
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• pp.17-28
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• 2005

A distributed constraint satisfaction problem (distributed CSP) is a constraint satisfaction problem (CSP) in which variables and constraints are distributed among multiple automated agents. A CSP is a problem to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of AI problems can be formalized as CSPs. Similarly, various application problems in DAI (Distributed AI) that are concerned with finding a consistent combination of agent actions can be formalized as distributed CPSs. The experimental results on example problems show that this algorithm is by far more efficient than the backtracking algorithm, in which the priority order is static. The priority order represents a hierarchy of agent authority, i.e., the priority of decision-marking. Therefore, these results imply that a flexible agent organization, in which the hierarchical order is changed dynamically, actually performs better than an organization in which the hierarchical order is static and rigid. Furthermore, we describe that the agent can be available to hold multiple variables in the searching scheme.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1298-1304
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• 2006

공급체인관리(Supply Chain Management)는 단순히 물질의 흐름관리뿐만 아니라 제품의 생산, 공급, 유통 등 다양하고 복잡한 활동들의 물질 및 정보 흐름의 통합이라고 할 수 있다. 그러므로 각 구성원간의 긴밀한 협력과 공동작업을 위해서는 원활한 정보 수집 및 응답이 요구된다. 하지만 기존 시스템은 비이동성 에이전트 개념으로 네트워크의 오버헤드나 혹은 접속 단절 상황에서 작업 수행이 불가능하여 구성원간의 정보 수집과 응답이 실제 업무 처리에 지연이 발생되므로 생산에서 판매까지의 리드타임이 길어지게 되고 채찍효과(Bullwhip Effect)가 더욱 크게 나타난다. 따라서 본 논문에서는 구성원간 협력과 공동작업을 위해 효율적으로 처리되어야 할 정보 수집 및 응답을 대상으로 하는 효율적 다중 응답을 위한 이동 에이전트 시스템을 설계한다. 제안시스템은 기존 시스템의 문제 해결을 위해 이동 에이전트와 객체 복제 메커니즘을 제시하며, 또한 각 구성원 시스템의 투명성을 위해 네이밍 서비스의 구성 방법과 등록된 구성원 시스템 객체의 객체 참조자 정보에 따라 복제된 이동 에이전트가 각 구성원 시스템으로 이주하는 이주 방식과 이주 후, 개별적인 작업 수행 결과를 해당 각 구성원 시스템에 제공하는 다중 응답 시나리오를 제시한다.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.123-131
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• 2006

Several distributed architectures, incorporating mobile agent technology, have been recently proposed to answer the scalability limitations of their centralized counterparts. However, these architectures fail to address scalability problems, when distributed tasks requiring the employment of itinerant agents is considered. This is because they lack mechanisms that guarantee optimization of agents' itineraries so as to minimize the total migration cost in terms of the round-trip latency and the incurred traffic. This is of particular importance when MAs itineraries span multiple subnets. The work presented herein aspires to address these issues. To that end, we have designed and implemented an algorithm that adapts methods usually applied for addressing network design problems in the specific area of mobile agent itinerary planning. The algorithm not only suggests the optimal number of mobile agents that minimize the overall cost but also constructs optimal itineraries for each of them. The algorithm implementation has been integrated into our mobile agent framework research prototype and tested in real network environments, demonstrating significant cost savings.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.151-178
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• 2006

The objective of this research is to develop a formal framework and methodology to facilitate real-time data integration, thus enabling semantic interoperability among distributed and heterogeneous information systems. The proposed approach is based on the concepts of "ontology" and "semantic mediators." An ontology is developed and used to capture the intension (including structure, integrity rules and meta-properties) of the database schema. We also develop the agent communication protocol for semantic reconciliation, which is based on the theory of speech acts and agent communication language. This protocol is used by a set of semantic mediators, which automatically detect and resolve various semantic conflicts at the data- and schema-levels by referring to the ontology. A mediation-based query processing technique is developed to provide uniform and integrated access to the multiple heterogeneous information sources. Prototype tools are being implemented to provide proof of concept for this work.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.1
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• pp.19-28
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• 2012

We consider a multi-agent scheduling problem such that each agent tries to maximize the weighted number of just-in-time jobs. Two objectives are considered : the first is to find the optimal solution for one agent with constraints on the other agents' weight functions, and the second is to find the largest set of efficient schedules of which corresponding objective vectors are different for the case with identical weights. We show that when the number of agents is fixed, the single machine case with the first objective is NP-hard in the ordinary sense, and present the polynomial- time algorithm for the two-machine flow shop case with the second objective and identical weights.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1359-1363
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• 2009

The object of this research is to develop a simulation system for earthmoving operations in consideration of the impact of congestion in-between equipment and existing traffic flow around the site. The congestion in-between equipment and traffic flow affect work productivity. The conventional discrete event simulation, however, has limitations in simulating the flow of construction equipment. To consider the impact of congestion in-between equipment and existing traffic flow, in this paper, a multi-agent based simulation model that can realize characteristics of truck behavior more accurately to consider the impact of congestion was proposed. In this simulation model, multiple agents can identify environmental changes and adapt themselves to the new environment. This modeling approach is a better choice for this problem since it describes behavioral characteristics of each agent by sensing changes in dynamic surroundings. This study suggests a detailed system design of the multi-agent based simulation system.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.125-132
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• 2003

The Internet reservation service is one of the most utilized internet services, specifically the agent efficiently supports this reservation services. The Agent will replace the repetitious reservation process and selectively offering the most proper service information. In this study, the user assisting agent system that can enable people to make reservation of public transportations through the internet is designed and implemented. This system consists of multiple agents that are Interface agent, 4ask agents and filtering agent. The interface agent is an arbitrator of this system that analyzes user's demand and integrate agent's result. And it has user-adaptive capability using case-based reasoning. There are three task agents if this system, it executes information gathering and information-change monitoring of each. Filtering agent extracts information only about reservation status in gathered information. Finally, this system is to offer integrated information of the reservation status about train and airplane and execute the simple-repetitious works for the reservation instead of user by agents.