• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제5권6호
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• pp.793-800
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• 1999

TMN Agent Platform은 망 요소의 운영상태와 자원들을 GDMO에 따라 관리객체(Managed Object : MO)로 모델링 하고, 자원들의 현재 상태를 유지하며, 관리자(Manager)로부터의 망 관리 기능 요구에 따라 조작된다. 그러므로, 에이전트의 성능향상은 전체적인 통신망 관리의 성능향상에 직접적인 영향을 미친다.본 논문에서는 TMN 에이전트의 기능요구 사항을 분석하고, 이를 토대로 성능향상을 위해 멀티스레드 기법을 사용하는 병렬 처리 구조의 TMN Agent Platform의 기능구조를 제시한다. 또한 에이전트와 다양한 자원들간의 효율적인 메시지전달을 위한 체계를 제시하며, 구현된 TMN Agent Platform의 성능을 분석한다.Abstract TMN Agent manages the operational status and real-resources of network elements, such as switching nodes and transmission systems. It performs the requested management functions from manager and maintains consistent status data of real-resource. The performance of agent system affects directly the performance of network management operation. If the agent is implemented by sequential processing scheme with single process, the agent processing can be delayed or blocked according to the status of real-resources. This problem can be solved by parallel and distributed processing scheme.To improve the processing performance of TMN Agent, we propose a TMN Agent Platform's functional architecture that is based on parallel processing with multi-tread and effective message transferring scheme between agent and various real-resource. We analyze the performance of the implemented TMN Agent Platform.

• 인지과학
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• 제10권1호
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• pp.1-11
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• 1999

최근 에이전트 기반 시스템 기술은 소프트웨어 시스템의 개념화, 설계, 구현을 위한 새로운 패러다임을 제공하며 많은 기대를 받아왔다. 특히 멀티 에이전트 시스템은 분산적이고 개방적인 인터넷 환경에 잘 부합되는 특징을 가지고 있어서 많은 연구가 진행되고 있다. 멀티 에이전트 시스템에서는 각 에이전트들이 자신의 목적을 위해 행동하기 때문에 에이전트간 충돌이 발생하는 경우에 조정을 통해 협력할 수 있어야 한다. 그러나 기존의 멀티 에이전트 시스템에서의 에이전트 간 협력 방법에 관한 연구 방법들은 동적 환경에서 서로 다른 목적을 갖는 에이전트간의 협동 문제를 올바로 해결할 수 없다는 문제가 있었다. 본 논문에서는 강화학습을 이용한 자동 역할 조정 방법을 통하여 에이전트가 처한 동적 환경에서 서로 다른 목적을 갖는 에이전트간의 협력 문제를 해결한다. 이를 위하여 멀티 에이전트 시스템 분야의 전통적인 문제인 추적 문제에 동적 환경과 서로 다른 목표를 갖는 에이전트들을 모델 링 하여, 두 가지 수정된 추적 문제를 제안하고 이 문제의 해결을 통하여 제안한 방법이 타당함을 보였다.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.622-626
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• 2012

This paper presents synchronization of LTV (Linear Time-Varying) MAS (Multi-Agent Systems) with heterogeneous time-varying disturbances under a fixed, connected, and undirected communication network. All the agents can collect only relative state information from their neighborhoods. To achieve synchronization of the MAS, an integral control scheme is proposed based on relative state information between agents.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• 한국지능시스템학회논문지
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• 제13권2호
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• pp.192-199
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• 2003

멀티에이전트 시스템에서 에이전트는 각자 달성해야 할 목표를 가지고 있다. 그러나 여러 에이전트들이 하나의 공통된 목표를 달성하기 위해 서로 경쟁을 하는 경우거나 혹은 각자의 서로 다른 목표를 달성하기 위해 제한된 자원을 사용해야 하는 경우 에이전트들은 서로 충돌할 수 있다. 충돌이 발생할 때 에이전트들은 각자의 목표를 달성하기 위해 다른 에이전트들과의 협상을 통해 목표의 충돌이 없는 일치 상황에 도달하도록 설계되어야 한다. 본 논문은 멀티에이전트 시스템에서 믿음(belief),소망(desire),그리고 의도(intention)로 설명되는 BDI 구조가 각 에이전트가 가져야 할 정신적 태도의 핵심 요소라고 가정하고, 이러한 구조를 가지는 BDI 에이전트를 논리 프로그래밍의 틀에서 표현한다. 또한 서로 다른 목표를 가진 BDI 에이전트들이 자원이 제한된 협동적인 분산 환경에서 상호간의 목표 충돌을 해결하기 위해 협상을 통해 각자의 문제를 해결하는 알고리즘을 제시한다. 마지막으로 본 논문에서 제안한 협상 알고리즘의 효과성을 검증하기 위하여 협상 메타언어로 구현한 예제 문제의 실험 결과를 기술한다.

• 산업공학
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• 제16권4호
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• pp.473-484
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• 2003

In this paper we deal with the logistics brokerage process in which a logistics agent intermediates between vehicle owners and shippers for matching empty vehicles and freights. Based on the Multi-Criteria Decision Making (MCDM) methodology, the proposed agent system matches the most preferred empty vehicle to the shipper and the most preferred freight to the vehicle owner. In the proposed agent system, an MCDM based sensitivity analysis is also used for supporting decision makers under negotiations. Among various MCDM methodologies, Analytic Hierarchy Process (AHP) is utilized in this paper. Although AHP is one of the most popular MCDM methodologies, AHP needs a number of pair-wise comparisons for assessing alternatives and hence may give excessive decision making burden to the decision makers. In this paper, in order to reduce the decision making burden, a preference function based estimation method is proposed. We can expect that the MCDM based logistics brokerage agent can be used as an efficient and effective tool for e-logistics marketplaces on the internet.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.292-297
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• 1999

Evolving in artificial agent is an extremely difficult problem, but on the other hand, a challenging task. At present the studies mainly centered on single agent learning problem. In our case, we use simulated soccer to investigate multi-agent cooperative learning. Consider the fundamental differences in learning mechanism, existing reinforcement learning algorithms can be roughly classified into two types-that based on evaluation functions and that of searching policy space directly. Genetic Programming developed from Genetic Algorithms is one of the most well known approaches belonging to the latter. In this paper, we give detailed algorithm description as well as data construction that are necessary for learning single agent strategies at first. In following step moreover, we will extend developed methods into multiple robot domains. game. We investigate and contrast two different methods-simple team learning and sub-group loaming and conclude the paper with some experimental results.

• Industrial Engineering and Management Systems
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• 제11권4호
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• pp.339-345
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• 2012

This research aims to formulate a mathematical model and develop an algorithm for solving a location problem in emergency medical service vehicle parking. To find an optimal parking location which has the least risk score or risk priority number calculated from severity, occurrence, detection, and distance from parking location for emergency patients, data were collected from Pratoom sub-district Disaster Prevention and Mitigation Center from October 2010 to April 2011. The criteria of risk evaluation were modified from Automotive Industry Action Group's criteria. An adaptive simulated annealing algorithm with multiple cooling schedules called multi-agent simulated quenching (MASQ) is proposed for solving the problem in two schemes of algorithms including dual agent and triple agent quenching. The result showed that the solution obtained from both scheme of MASQ was better than the traditional solution. The best locations obtained from MASQ-dual agent quenching scheme was nodes #5 and #133. The risk score was reduced 61% from 6,022 to 2,371 points.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2023-2028
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• 2004

This paper reveals the utilization of the multi-gent system that based on the Blackboard system basis as the controller of Soccer Robot. This system is a portion of developing the Soccer Robot team for Robocup 2004 Competition. In this development, the intelligent control system was initiated by the combination of parallel and distributed blackboard structures with the principle design that generated from human body structures, which consists of the combination of two main systems, the organs system and the brain system. The system is designed using the control system theory based on Blackboard basis. Modification of the initial structures to corroborate the Soccer Robot and the structure's constituents are clarified accordingly. To demonstrate the idea, ITE-old team is given as a case study.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.156-163
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• 2001

Business forecasting is vital to the success of business. There has been an increasing demand for building business forecasting software system to assist human being to do forecasting. However, the uncertain and complex nature makes is a challenging work to analyze, design and implement software solutions for business forecasting. Traditional forecasting systems in which their models are trained based on small collection of historical data could not meet such challenges at the information explosion over the Internet. This paper presents an agent oriented business forecasting approach for building intelligent business forecasting software systems with high reusability. Although agents have been applied successfully to many application domains. little work has been reported to use the emerging agent oriented technology of this paper is that it explores how agent can be used to help human to manage various business forecasting processes in the whole business forecasting life cycle.