• The KIPS Transactions:PartA
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• v.16A no.1
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• pp.1-8
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• 2009

Ubiquitous computing requires an intelligent environment where the users do not need to be involved in the operation. The agent technology allows effective implementation of ubiquitous system, while agent platform provides efficient and stable interaction between the agents. In this paper we propose a hierarchical P2P networking approach where the messages are combined inside the agent platform and then compressed in two levels. The proposed approach capitalizes the static nature of the messages of typical context-aware applications. Experiment with an actual multi-agent system reveals that the response time and throughput are significantly improved compared to the existing scheme.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.377-384
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• 2003

B2B EC에서 지능형 에이전트에 대한 요구의 증가와 함께 기업구매자가 직접 전자시장으로부터 구매하는 데스크탑 구매의 요구도 증가하고 있는 추세이다. 본 논문에서는 B2B 상에서 전자시장으로부터의 효율적인 구매를 지원하는 b-Cart 기반 에이전트 시스템의 설계 사례에 대해서 기술한다. b-Cart는 구매자가 소유하고 사용되는 구매자 사이트에 위치한 쇼핑카트로서, 본 논문에서는 B2B EC에서의 b-Cart 기반 에이전트 시스템의 요구 기능을 사용자식별(Identification), 사용자 다이알로그(User Dialog), 상품정보수집(Collection), 물품정보제거(Trashing), 개별 구매의사결정지원(Individual Purchase Decision Support), 조직 구매의사결정지원(Organizational Purchase Decision Support), 협상(Negotiation), 주문처리(Ordering), 지불처리(Payment), 진행사항 추적(Tracking), 구매기록(Recording), 전자구매시스템에 구매기록 전송(Record Transmission), 지식베이스에 새로운 지식 유지(Knowledge Maintenance)으로 정의하고, b-Cart 기반 에이전트 시스템의 메시지 인터페이스를 설계하고 시스템의 구조를 설계하여 프로토타입 시스템인 AgentB의 설계 사례를 소개한다. b-Cart 기반 에이전트시스템은 기업구매자의 전자시장으로부터 구매자 증가함에 따라 분산된 정보를 관리 해주고 통합적으로 구매처리를 해줄수 있는 효과적인 시스템이다. 향 후 B2B EC의 에이전트 시스템은 b-Cart를 기반으로 할 것으로 예측할 수 있다.

• ETRI Journal
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• v.44 no.2
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• pp.313-326
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• 2022

This study presents a noble scheme for distributed and parallel simulations with optimized agent placement for simulation instances. The traditional parallel simulation has some limitations in that it does not provide sufficient performance even though using multiple resources. The main reason for this discrepancy is that supporting parallelism inevitably requires additional costs in addition to the base simulation cost. We present a comprehensive study of parallel simulation architectures, execution flows, and characteristics. Then, we identify critical challenges for optimizing large simulations for parallel instances. Based on our cost-benefit analysis, we propose a novel approach to overcome the performance constraints of agent-based parallel simulations. We also propose a solution for eliminating the synchronizing cost among local instances. Our method ensures balanced performance through optimal deployment of agents to local instances and an adaptive agent placement scheme according to the simulation load. Additionally, our empirical evaluation reveals that the proposed model achieves better performance than conventional methods under several conditions.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.467-474
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• 2001

When user wants to animate more than one character, some unexpected motion animation like a collision between characters may occur. Therefore, this problem must be resolved using a proper control mechanism. Therefore, this problem must be resolved using a proper control mechanism. This paper proposes an agent-based system that controls the motion animation of the character for representing animation scenario reflecting user\`s intention. This system provides a method that coordinates a type of motion and avoids collision between characters according to the moving path of a character in three-dimensional space. Agent communicates with others for motion synchronization. Agent is extended into several intelligent agents that coordinate character\`s motion. Agent system enables not only an intended motion animation, but also the scheduling of motion to an entire character animation. It designs automata model using Petri-net analysis tool for the agent\`s interaction as a method that passes the agent\`s information and infers the current state of agents. We implement this agent system to control the motion of character using agent technology and show an example of controlling the motion of human character model to prove the possiblity of motion control.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.35-41
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• 2003

A multi-agent technology has emerged as a new paradigm that can flexibly and promptly cope with various environmental changes and complex problems. Accordingly, many researches are being made to establish multi-agent systems in an effort to solve dynamic problems in many fields. However, most previous researches on the multi-agent frameworks aimed at, on behalf of a user, exchanging and sharing information between agents, reusing agents, and suggesting job cooperation in order to integrate and assimilate heterogeneous agents. That is to say, their frameworks mainly focused on the basic functions of general multi-agent. Therefore, they are not suitable to the development of the proper system for a specific field such ,.s a negotiation. In an effort to solve this problem, this research has tried to design a multi-agent framework-base negotiation system, so that for the sake of a user it can evaluate the negotiation messages, manage the negotiation messages, and quickly and exactly exchange messages between negotiation agents. First of all, we have made research on the basic functions hat are necessary in the development of a negotiation system, and then have analyzed the limitations of existing multi-agent frameworks when trying to apply them to a negotiation system. After these efforts, this study suggests a design of multi-agent framework to develop a negotiation system.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.205-227
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• 2002

Our study is focused on a multiple-agent system to provide efficient collaborative work by automating the conference calling process with the help of intelligent agents. Automating the meeting scheduling requires a careful consideration of the individual official schedule as well as the privacy and personal preferences. Therefore, the automation of conference calling needs the distributed processing task where a separate calendar management process is associated for increasing the reliability and inherent parallelism. This paper describes in detail the design and implementation issues of a multiple-agent system for conference calling that allows the convener and participants to minimize their efforts in creating a meeting. Our system is based on the client-sewer model. In the sewer side, a scheduling agent, a negotiating agent, a personal information managing agent, a group information managing agent, a session managing agent, and a coordinating agent are operating. In the client side, an interface agent, a media agent, and a collaborating agent are operating. Agents use a standardized knowledge manipulation language to communicate amongst themselves. Communicating through a standardized knowledge manipulation language allows the system to overcome heterogeneity which is one of the most important problems in communication among agents for distributed collaborative computing. The agents of our system propose the dates on which as many participants as possible are available to attend the conference using the forward chaining algorithm and the back propagation network algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.239-243
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• 2003

Recently, there has been active research conducted on the intelligent agent in various fields. The results have been widely applied to intelligent user-friendly interfaces. In this system, we modeled, designed, and implemented an intelligent agent system that can be applied to stock and news. Some procedures such as login sequence to the web site, process to get stock information, setting stock in concern, intelligent news system module, news analysis module, and news learning module are modeled in detail and described in block diagram level. In our experiment on stock system, it showed quite a useful alarming screen avatar result and also on news system. it successfully rearranged the order of the news according to the user's preferences.

• Information Systems Review
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• v.4 no.2
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• pp.223-236
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• 2002

In an agent-based system, each agent has its own decision making capability and competes, cooperates, and communicates each other with an agent interface. Virtual manufacturing has characteristics as a typical application area of agent-based system: complex and time-bound decision making and negotiation. The time-boundness influences the choice of decision making models and design of protocols for internal and external negotiation. In this paper, we provide a case study which suggests a time-bound framework for external and internal negotiation between the agents for virtual manufacturing environment. We illustrate decision making model selection strategy and the system architecture of the agent-based system for the complex and time-bound environment.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.814-826
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• 2005

The user-centric broadcasting environment includes the agent system and personalized broadcasting services for user-adaptive TV watching. In this paper, we propose broadcasting environment consisting of personalized broadcasting services and a multi-agent broadcasting system for the services. The proposed system employs the intelligent agent technology of the Foundation for Intelligent Physical Agents (FIPA) as well as metadata technology of MPEG-7 and TV-Anytime Forum (TVAF). To verify the usefulness of the proposed environment, we implemented a test-bed and demonstrated the proposed agent system with three services including intelligent user-information management service, information mobility service, and content retrieval service.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.5
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• pp.49-57
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• 2008

In this paper, we suggested a methodology that can be used by an agent to learn models of other agents in a multi-agent system. To construct these model, we used influence diagram as a modeling tool. We present a method for learning models of the other agents at the decision nodes, value nodes, and chance nodes in influence diagram. We concentrated on learning of the other agents at the value node by using neural network learning technique. Furthermore, we treated anti-air units in anti-air defense domain as agents in multi. agent system.