• 한국컴퓨터정보학회논문지
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• 제10권3호
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• pp.339-344
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• 2005

현재 오프라인 신용카드 가맹점에서의 신용카드 결제 시에 사용되는 결제 시스템은 신용카드 결제 단말기, 결제 중계 서비스를 하는 VAN사 그리고 신용카드사로 구성되어 있다. 신용카드사 장애 시에는 결제 중계 서비스 VAN사가 승인 대행을 하여 처리하나, 결제 중계 서비스 VAN사 장애 시에는 신용카드 결제 서비스가 원활하게 이루어지지 않는다. 본 논문은 신용카드 결제 단말기에 결제 중계 서비스를 하는 VAN사의 장애 시에 Switching Agent를 이용하여 또 다른 서비스 VAN사에서 결제 중계 서비스를 할 수 있도록 하는 신용카드 결제 시스템을 제안하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.170-175
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• 1998

Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.401-406
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• 2012

This paper considers multi-agent systems with interval time-varying delays and switching interconnection topology. By construction of a suitable Lyapunov-Krasovskii's functional, new delay-dependent consensus control conditions for the systems are established in terms of LMIs (Linear Matrix Inequalities) which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the effectiveness of the proposed methods.

• 한국산업정보학회논문지
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• 제4권3호
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• pp.44-51
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• 1999

본 논문에서는 ATM 교환기 TMN EMS의 성능 분석을 위한 큐잉 모델을 제시한다. ATM교환기 관리를 위한 TMN 시스템은 관리자, 대행자, ATM교환기 등이 계층적인 구조로 이루어져 있다. 관리자는 여러개의 대행자와 통신하며, 대행자는 ATM 교환기의 관리 기능을 대행한다. 우리는 EMS를 구성하는 관리자의 용량과 성능을 예측하기 위하여 큐잉 모델을 정의하였다. 이 모델을 통하여 EMS의 평균 서비스 시간과 용량을 예측할 수 있다.

• 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.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1074-1082
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• 2020

Recently, research has been actively conducted to create artificial intelligence agents that learn games through reinforcement learning. There are several factors that determine performance when the agent learns a game, but using any of the activation functions is also an important factor. This paper compares and evaluates which activation function gets the best results if the agent learns the game through reinforcement learning in the 2D racing game environment. We built the agent using a reinforcement learning algorithm and a neural network. We evaluated the activation functions in the network by switching them together. We measured the reward, the output of the advantage function, and the output of the loss function while training and testing. As a result of performance evaluation, we found out the best activation function for the agent to learn the game. The difference between the best and the worst was 35.4%.

• 한국정보통신학회논문지
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• 제9권8호
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• pp.1847-1854
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• 2005

기존 VoD 시스템의 멀티캐스트 방법은 사용자의 요청수가 증가함에 따라 시스템 부하가 증가하게 되어 시스템의 성능이 떨어지게 된다. 본 논문에서는 사용자들이 빈번하게 요청하는 인기비디오에 대한 정보를 프록시 서버에 저장 관리하여, 사용자들의 비디오 요청 시 발생하는 네트워크의 사용과 서버의 부하를 줄이는 방법에 대해 연구하였다. 본 논문에서는 효율적인 VoD 서비스를 위해 멀터 프록시(Multi-Proxies)들을 관리하는 Interchange Agent(IA)를 구축하였다. 이를 위해, 멀티캐스팅 기법을 이용하여 사용자의 동일 비디오 요청을 하나로 묶어 처리하여 네트워크 및 서버의 부하를 줄고, 자신의 리스트를 이용하여 멀티프록시 캐시의 내용을 중복 없이 관리하여 시스템 효율을 높이며, 스위칭 기능을 통하여 사용자가 요청한 비디오가 연결된 다른 프록시에 존재하면 이를 스위칭 채널을 통해 즉시 전송하여 실시간 서비스의 효율을 높이고, 각 프록시 캐시의 임시저장장소와 카운터를 이용하여 사용자의 인기비디오 순위 변경 시, 캐시의 내용을 변경하여 그 흐름을 반영하도록 하였다.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.439-444
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• 2012

In this study, we address the formation control problem of coupled unicycle-type mobile robots, each of which can interact with its neighboring robots by communicating their position outputs. Each communication link between two mobile robots is assumed to be established according to the given time-varying interconnection topology that switches within a finite set of connected fixed undirected networks and has a non-vanishing dwell time. Under this setup, we propose a distributed formation control algorithm by using the dynamics extension and feedback linearization methods, and by employing a consensus algorithm for linear multi-agent systems which provides arbitrary fast convergence rate to the agreement of the multi-agent system. Finally, the proposed result is demonstrated through a computer simulation.

• 문화기술의 융합
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• 제9권3호
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• pp.797-802
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• 2023

영어가 외국어로서 사용되는 환경에서 영어 말하기 연습 활동에 AI 음성 챗봇을 사용했을 때 영어학습자들은 발화 동기가 높아지고 의사소통 연습의 기회가 많아져 결과적으로 영어 말하기 능력을 향상 시킬 수 있다. 본 연구에서는 초등학생 저학년의 경우에도 쉽게 활용 가능하고 학습효과를 높일 수 있는 가르치기 방식의 AI 음성 챗봇을 제안한다. 시제와 맥락과 기억에 기반한 활동인 언어학습에 Teachable Agent 시스템을 적용하기 위해 Teachable Agent에 학습자의 영어 발음과 수준을 반영하고, 학습자 오류에 맞추어 에이전트의 답변을 생성하는 방식을 적용하여 새로운 방식의 TA를 제안하고 이를 적용한 Teachable Agent AI 챗봇 프로토타입을 구현하였다. 실제 초등 영어 선생님과 초등학생을 대상으로 사용성 평가를 진행하여 학습 효과를 입증하였다. 본 연구 결과는 역할 전환을 통해 학습에 흥미가 없는 학생 또는 초등 저학년들이 학습에 스스로 참여할 수 있는 동기부여를 할 수 있도록 적용할 수 있다.

• Asia pacific journal of information systems
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• 제20권1호
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• pp.127-140
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• 2010

The benefit that a consumer derives from the use of a good often depends on the number of other consumers purchasing the same goods or other compatible items. This property, which is known as network externality, is significant in many IT related industries. Over the past few decades, network externalities have been recognized in the context of physical networks such as the telephone and railroad industries. Today, as many products are provided as a form of system that consists of compatible components, the appreciation of network externality is becoming increasingly important. Network externalities have been extensively studied among economists who have been seeking to explain new phenomena resulting from rapid advancements in ICT (Information and Communication Technology). As a result of these efforts, a new body of theories for 'New Economy' has been proposed. The theoretical bottom-line argument of such theories is that technologies subject to network effects exhibit multiple equilibriums and will finally lock into a monopoly with one standard cornering the entire market. They emphasize that such "tippiness" is a typical characteristic in such networked markets, describing that multiple incompatible technologies rarely coexist and that the switch to a single, leading standard occurs suddenly. Moreover, it is argued that this standardization process is path dependent, and the ultimate outcome is unpredictable. With incomplete information about other actors' preferences, there can be excess inertia, as consumers only moderately favor the change, and hence are themselves insufficiently motivated to start the bandwagon rolling, but would get on it once it did start to roll. This startup problem can prevent the adoption of any standard at all, even if it is preferred by everyone. Conversely, excess momentum is another possible outcome, for example, if a sponsoring firm uses low prices during early periods of diffusion. The aim of this paper is to analyze the dynamics of the adoption process in markets exhibiting network effects by focusing on two factors; switching and agent heterogeneity. Switching is an important factor that should be considered in analyzing the adoption process. An agent's switching invokes switching by other adopters, which brings about a positive feedback process that can significantly complicate the adoption process. Agent heterogeneity also plays a important role in shaping the early development of the adoption process, which has a significant impact on the later development of the process. The effects of these two factors are analyzed by developing an agent-based simulation model. ABM is a computer-based simulation methodology that can offer many advantages over traditional analytical approaches. The model is designed such that agents have diverse preferences regarding technology and are allowed to switch their previous choice. The simulation results showed that the adoption processes in a market exhibiting networks effects are significantly affected by the distribution of agents and the occurrence of switching. In particular, it is found that both weak heterogeneity and strong network effects cause agents to start to switch early and this plays a role of expediting the emergence of 'lock-in.' When network effects are strong, agents are easily affected by changes in early market shares. This causes agents to switch earlier and in turn speeds up the market's tipping. The same effect is found in the case of highly homogeneous agents. When agents are highly homogeneous, the market starts to tip toward one technology rapidly, and its choice is not always consistent with the populations' initial inclination. Increased volatility and faster lock-in increase the possibility that the market will reach an unexpected outcome. The primary contribution of this study is the elucidation of the role of parameters characterizing the market in the development of the lock-in process, and identification of conditions where such unexpected outcomes happen.